ÿþ<html xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40"> <head><script src="//archive.org/includes/analytics.js?v=cf34f82" type="text/javascript"></script> <script type="text/javascript">window.addEventListener('DOMContentLoaded',function(){var v=archive_analytics.values;v.service='wb';v.server_name='wwwb-app221.us.archive.org';v.server_ms=634;archive_analytics.send_pageview({});});</script> <script type="text/javascript" src="/_static/js/bundle-playback.js?v=poeZ53Bz" charset="utf-8"></script> <script type="text/javascript" src="/_static/js/wombat.js?v=UHAOicsW" charset="utf-8"></script> <script type="text/javascript"> __wm.init("https://web.archive.org/web"); __wm.wombat("http://www.orlabanalytics.ca/icaor/icaor13_abstracts.htm","20200712151021","https://web.archive.org/","web","/_static/", "1594566621"); </script> <link rel="stylesheet" type="text/css" href="/_static/css/banner-styles.css?v=fantwOh2" /> <link rel="stylesheet" type="text/css" href="/_static/css/iconochive.css?v=qtvMKcIJ" /> <!-- End Wayback Rewrite JS Include --> <meta http-equiv="Content-Type" content="text/html; charset=unicode"> <meta name="ProgId" content="Word.Document"> <meta name="Generator" content="Microsoft Word 12"> <meta name="Originator" content="Microsoft Word 12"> <link rel="File-List" href="icaor13_abstracts_files/filelist.xml"> <link rel="Edit-Time-Data" href="icaor13_abstracts_files/editdata.mso"> <!--[if !mso]> <style> v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} </style> <![endif]--> <title>ICAOR 2013 ABSTRACTS</title> <link rel="themeData" href="icaor13_abstracts_files/themedata.thmx"> <link rel="colorSchemeMapping" href="icaor13_abstracts_files/colorschememapping.xml"> <!--[if gte mso 9]><xml> <w:WordDocument> <w:SpellingState>Clean</w:SpellingState> <w:GrammarState>Clean</w:GrammarState> <w:TrackMoves>false</w:TrackMoves> <w:TrackFormatting/> <w:ValidateAgainstSchemas/> <w:SaveIfXMLInvalid>false</w:SaveIfXMLInvalid> <w:IgnoreMixedContent>false</w:IgnoreMixedContent> <w:AlwaysShowPlaceholderText>false</w:AlwaysShowPlaceholderText> <w:DoNotPromoteQF/> <w:LidThemeOther>EN-US</w:LidThemeOther> <w:LidThemeAsian>X-NONE</w:LidThemeAsian> <w:LidThemeComplexScript>X-NONE</w:LidThemeComplexScript> <w:Compatibility> <w:BreakWrappedTables/> <w:SnapToGridInCell/> <w:WrapTextWithPunct/> <w:UseAsianBreakRules/> <w:DontGrowAutofit/> <w:SplitPgBreakAndParaMark/> <w:DontVertAlignCellWithSp/> <w:DontBreakConstrainedForcedTables/> <w:DontVertAlignInTxbx/> <w:Word11KerningPairs/> <w:CachedColBalance/> </w:Compatibility> <w:BrowserLevel>MicrosoftInternetExplorer4</w:BrowserLevel> <m:mathPr> <m:mathFont m:val="Cambria Math"/> <m:brkBin m:val="before"/> <m:brkBinSub m:val="&#45;-"/> <m:smallFrac m:val="off"/> <m:dispDef/> <m:lMargin m:val="0"/> <m:rMargin m:val="0"/> <m:defJc m:val="centerGroup"/> <m:wrapIndent m:val="1440"/> <m:intLim m:val="subSup"/> <m:naryLim m:val="undOvr"/> </m:mathPr></w:WordDocument> </xml><![endif]--><!--[if gte mso 9]><xml> <w:LatentStyles DefLockedState="false" DefUnhideWhenUsed="true" DefSemiHidden="true" DefQFormat="false" DefPriority="99" LatentStyleCount="267"> <w:LsdException Locked="false" Priority="0" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Normal"/> <w:LsdException Locked="false" Priority="9" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="heading 1"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 2"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 3"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 4"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 5"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 6"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 7"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 8"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 9"/> <w:LsdException Locked="false" Priority="39" Name="toc 1"/> <w:LsdException Locked="false" Priority="39" Name="toc 2"/> <w:LsdException Locked="false" Priority="39" Name="toc 3"/> <w:LsdException Locked="false" Priority="39" Name="toc 4"/> <w:LsdException Locked="false" Priority="39" Name="toc 5"/> <w:LsdException Locked="false" Priority="39" Name="toc 6"/> <w:LsdException Locked="false" Priority="39" Name="toc 7"/> <w:LsdException Locked="false" Priority="39" Name="toc 8"/> <w:LsdException Locked="false" Priority="39" Name="toc 9"/> <w:LsdException Locked="false" Priority="35" QFormat="true" Name="caption"/> <w:LsdException Locked="false" Priority="10" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Title"/> <w:LsdException Locked="false" Priority="1" Name="Default Paragraph Font"/> <w:LsdException Locked="false" Priority="11" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Subtitle"/> <w:LsdException Locked="false" Priority="22" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Strong"/> <w:LsdException Locked="false" Priority="20" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Emphasis"/> <w:LsdException Locked="false" Priority="59" SemiHidden="false" UnhideWhenUsed="false" Name="Table Grid"/> <w:LsdException Locked="false" UnhideWhenUsed="false" Name="Placeholder Text"/> <w:LsdException Locked="false" Priority="1" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="No Spacing"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false" UnhideWhenUsed="false" Name="Light Shading"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false" UnhideWhenUsed="false" Name="Light List"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false" UnhideWhenUsed="false" Name="Light Grid"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 1"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 2"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 1"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 2"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 1"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 2"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 3"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false" UnhideWhenUsed="false" Name="Dark List"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Shading"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful List"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Grid"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false" UnhideWhenUsed="false" Name="Light Shading Accent 1"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false" UnhideWhenUsed="false" Name="Light List Accent 1"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false" UnhideWhenUsed="false" Name="Light Grid Accent 1"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 1 Accent 1"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 2 Accent 1"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 1 Accent 1"/> <w:LsdException Locked="false" UnhideWhenUsed="false" Name="Revision"/> <w:LsdException Locked="false" Priority="34" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="List Paragraph"/> <w:LsdException Locked="false" Priority="29" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Quote"/> <w:LsdException Locked="false" Priority="30" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Intense Quote"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 2 Accent 1"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 1 Accent 1"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 2 Accent 1"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 3 Accent 1"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false" UnhideWhenUsed="false" Name="Dark List Accent 1"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Shading Accent 1"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful List Accent 1"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Grid Accent 1"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false" UnhideWhenUsed="false" Name="Light Shading Accent 2"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false" UnhideWhenUsed="false" Name="Light List Accent 2"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false" UnhideWhenUsed="false" Name="Light Grid Accent 2"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 1 Accent 2"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 2 Accent 2"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 1 Accent 2"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 2 Accent 2"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 1 Accent 2"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 2 Accent 2"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 3 Accent 2"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false" UnhideWhenUsed="false" Name="Dark List Accent 2"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Shading Accent 2"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful List Accent 2"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Grid Accent 2"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false" UnhideWhenUsed="false" Name="Light Shading Accent 3"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false" UnhideWhenUsed="false" Name="Light List Accent 3"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false" UnhideWhenUsed="false" Name="Light Grid Accent 3"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 1 Accent 3"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 2 Accent 3"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 1 Accent 3"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 2 Accent 3"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 1 Accent 3"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 2 Accent 3"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 3 Accent 3"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false" UnhideWhenUsed="false" Name="Dark List Accent 3"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Shading Accent 3"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful List Accent 3"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Grid Accent 3"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false" UnhideWhenUsed="false" Name="Light Shading Accent 4"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false" UnhideWhenUsed="false" Name="Light List Accent 4"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false" UnhideWhenUsed="false" Name="Light Grid Accent 4"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 1 Accent 4"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 2 Accent 4"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 1 Accent 4"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 2 Accent 4"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 1 Accent 4"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 2 Accent 4"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 3 Accent 4"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false" UnhideWhenUsed="false" Name="Dark List Accent 4"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Shading Accent 4"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful List Accent 4"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Grid Accent 4"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false" UnhideWhenUsed="false" Name="Light Shading Accent 5"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false" UnhideWhenUsed="false" Name="Light List Accent 5"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false" UnhideWhenUsed="false" Name="Light Grid Accent 5"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 1 Accent 5"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 2 Accent 5"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 1 Accent 5"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 2 Accent 5"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 1 Accent 5"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 2 Accent 5"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 3 Accent 5"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false" UnhideWhenUsed="false" Name="Dark List Accent 5"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Shading Accent 5"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful List Accent 5"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Grid Accent 5"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false" UnhideWhenUsed="false" Name="Light Shading Accent 6"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false" UnhideWhenUsed="false" Name="Light List Accent 6"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false" UnhideWhenUsed="false" Name="Light Grid Accent 6"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 1 Accent 6"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Shading 2 Accent 6"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 1 Accent 6"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false" UnhideWhenUsed="false" Name="Medium List 2 Accent 6"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 1 Accent 6"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 2 Accent 6"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false" UnhideWhenUsed="false" Name="Medium Grid 3 Accent 6"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false" UnhideWhenUsed="false" Name="Dark List Accent 6"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Shading Accent 6"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful List Accent 6"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false" UnhideWhenUsed="false" Name="Colorful Grid Accent 6"/> <w:LsdException Locked="false" Priority="19" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Subtle Emphasis"/> <w:LsdException Locked="false" Priority="21" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Intense Emphasis"/> <w:LsdException Locked="false" Priority="31" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Subtle Reference"/> <w:LsdException Locked="false" Priority="32" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Intense Reference"/> <w:LsdException Locked="false" Priority="33" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Book Title"/> <w:LsdException Locked="false" Priority="37" Name="Bibliography"/> <w:LsdException Locked="false" Priority="39" QFormat="true" Name="TOC Heading"/> </w:LatentStyles> </xml><![endif]--> <style> <!-- DIV[class="Sect"] { text-align:left; margin-bottom:0px; margin-top:0px; margin-right:0px; margin-left:0px; text-indent:0px; direction:ltr } table {display:inline-table; float:none;} /* Font Definitions */ @font-face {font-family:"Cambria Math"; panose-1:2 4 5 3 5 4 6 3 2 4; mso-font-charset:1; mso-generic-font-family:roman; mso-font-format:other; mso-font-pitch:variable; mso-font-signature:0 0 0 0 0 0;} @font-face {font-family:Cambria; panose-1:2 4 5 3 5 4 6 3 2 4; mso-font-charset:0; mso-generic-font-family:roman; mso-font-pitch:variable; mso-font-signature:-536870145 1073743103 0 0 415 0;} @font-face {font-family:Tahoma; panose-1:2 11 6 4 3 5 4 4 2 4; mso-font-charset:0; mso-generic-font-family:swiss; mso-font-pitch:variable; mso-font-signature:-520081665 -1073717157 41 0 66047 0;} /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-unhide:no; mso-style-qformat:yes; mso-style-parent:""; margin:0cm; margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman","serif"; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; color:black;} h1 {mso-style-priority:9; mso-style-unhide:no; mso-style-qformat:yes; mso-style-link:"Heading 1 Char"; margin-top:0cm; margin-right:0cm; margin-bottom:11.25pt; margin-left:0cm; text-align:center; mso-pagination:widow-orphan; mso-outline-level:1; font-size:24.0pt; font-family:"Times New Roman","serif"; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; color:black; font-weight:bold;} h2 {mso-style-noshow:yes; mso-style-priority:9; mso-style-qformat:yes; mso-style-link:"Heading 2 Char"; margin-top:0cm; margin-right:0cm; margin-bottom:24.0pt; margin-left:0cm; text-align:justify; mso-pagination:widow-orphan; mso-outline-level:2; font-size:18.0pt; font-family:"Times New Roman","serif"; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; color:black; font-weight:bold;} a:link, span.MsoHyperlink {mso-style-noshow:yes; mso-style-priority:99; color:blue; text-decoration:underline; text-underline:single;} a:visited, span.MsoHyperlinkFollowed {mso-style-noshow:yes; mso-style-priority:99; color:purple; text-decoration:underline; text-underline:single;} p {mso-style-noshow:yes; mso-style-priority:99; margin:0cm; margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman","serif"; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; color:black;} p.MsoAcetate, li.MsoAcetate, div.MsoAcetate {mso-style-noshow:yes; mso-style-priority:99; mso-style-link:"Balloon Text Char"; margin:0cm; margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:8.0pt; font-family:"Tahoma","sans-serif"; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; color:black;} span.Heading1Char {mso-style-name:"Heading 1 Char"; mso-style-priority:9; mso-style-unhide:no; mso-style-locked:yes; mso-style-link:"Heading 1"; mso-ansi-font-size:24.0pt; mso-bidi-font-size:24.0pt; font-family:"Times New Roman","serif"; mso-ascii-font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:"Times New Roman"; mso-bidi-font-family:"Times New Roman"; color:black; mso-font-kerning:18.0pt; font-weight:bold;} span.Heading2Char {mso-style-name:"Heading 2 Char"; mso-style-noshow:yes; mso-style-priority:9; mso-style-unhide:no; mso-style-locked:yes; mso-style-link:"Heading 2"; mso-ansi-font-size:18.0pt; mso-bidi-font-size:18.0pt; font-family:"Times New Roman","serif"; mso-ascii-font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:"Times New Roman"; mso-bidi-font-family:"Times New Roman"; color:black; font-weight:bold;} span.BalloonTextChar {mso-style-name:"Balloon Text Char"; mso-style-noshow:yes; mso-style-priority:99; mso-style-unhide:no; mso-style-locked:yes; mso-style-link:"Balloon Text"; mso-ansi-font-size:8.0pt; mso-bidi-font-size:8.0pt; font-family:"Tahoma","sans-serif"; mso-ascii-font-family:Tahoma; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Tahoma; mso-bidi-font-family:Tahoma; color:black;} span.SpellE {mso-style-name:""; mso-spl-e:yes;} span.GramE {mso-style-name:""; mso-gram-e:yes;} .MsoChpDefault {mso-style-type:export-only; mso-default-props:yes; font-size:10.0pt; mso-ansi-font-size:10.0pt; mso-bidi-font-size:10.0pt;} @page WordSection1 {size:612.0pt 792.0pt; margin:72.0pt 72.0pt 72.0pt 72.0pt; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;} div.WordSection1 {page:WordSection1;} --> </style> <!--[if gte mso 10]> <style> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} </style> <![endif]--> <meta name="DC.Creator" content="Microsoft Office Word 2007"> <meta name="DC.Date" content="2013-06-13T01:41:39-07:00"> <meta name="DC.Date.Modified" content="2013-06-13T01:42:40-07:00"> <!--[if gte mso 9]><xml> <o:shapedefaults v:ext="edit" spidmax="15362"/> </xml><![endif]--><!--[if gte mso 9]><xml> <o:shapelayout v:ext="edit"> <o:idmap v:ext="edit" data="1"/> </o:shapelayout></xml><![endif]--> </head> <body bgcolor="white" lang="EN-US" link="blue" vlink="purple" style="tab-interval:36.0pt" alink="fushia"> <div class="WordSection1"> <div> <h1 align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext">ICAOR 2013 ABSTRACTS<o:p></o:p></span></h1> <p><b style="mso-bidi-font-weight:normal"><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext;mso-no-proof:yes">5<sup>TH</sup> </span></b><b style="mso-bidi-font-weight:normal"><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext">INTERNATIONAL CONFERENCE ON APPLIED OPERATIONAL RESEARCH<o:p></o:p></span></b></p> <p><b style="mso-bidi-font-weight:normal"><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext">29-31 JULY 2013, LISBON, PORTUGAL<o:p></o:p></span></b></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">APPLYING A SAVINGS ALGORITHM FOR SOLVING A RICH VEHICLE ROUTING PROBLEM IN A REAL URBAN CONTEXT <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">José <span class="SpellE">Cáceres</span>-Cruz, Daniel <span class="SpellE">Riera</span>, Roman <span class="SpellE">Buil</span> and Angel A. Juan<o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">IN3-Computer Science Department, Open University of Catalonia, Barcelona, Spain </span><span style="font-size: 9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Department of Telecommunications and Systems Engineering, <span class="SpellE">Universitat</span> <span class="SpellE">Autònoma</span> de Barcelona, <span class="SpellE">Bellaterra</span>, Spain </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> Nowadays urban transportation is a strategic domain for distribution companies. In academic literature, this problem is categorized as a Vehicle Routing Problem, a popular research stream that has undergone significant theoretical advances but has remained far from practice implementations. In fact, a general combinatorial routing problem has emerged as Rich Vehicle Routing Problem for considering problems inspired in real situations. Intra-urban distribution required a special combination of routing characteristics. In this study, we consider a routing problem with asymmetric cost matrix, heterogeneous fleet of vehicles, service times, limited routes length, open routes, and balanced loads in routes restrictions. Our objective function is to reduce the total traveling time. We present an algorithm based on a randomized Clarke &amp; Wright s Savings heuristic. We execute our algorithm with data from a company that distributes prepared food to more than 50 customers in Barcelona. The results reveal promising improvements in different scenarios.<o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">A STOCHASTIC BIOLOGICALLY-INSPIRED METAHEURISTIC FOR MODELLING-TO-GENERATE-ALTERNATIVES <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Julian Scott <span class="SpellE">Yeomans</span>, <span class="SpellE">Raha</span> <span class="SpellE">Imanirad</span> and <span class="SpellE">Xin</span>-She Yang<o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">OMIS Area, <span class="SpellE">Schulich</span> School of Business, York University, Toronto, ON, Canada </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">School of Science and Technology, Middlesex University, London, UK </span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> In solving many  real world decision-making applications, it is generally preferable to formulate several quantifiably good alternatives that provide numerous, distinct approaches to the problem. This is because policy formulation typically involves complex problems that are riddled with incongruent performance objectives and possess incompatible design requirements that can be very difficult  if not impossible  to incorporate at the time supporting decision models are constructed. By generating a set of maximally different solutions, it is believed that some of the dissimilar alternatives will provide unique perspectives that serve to satisfy the <span class="SpellE">unmodelled</span> characteristics. This maximally different solution creation approach is referred to as <span class="SpellE">modelling</span>-to-generate-alternatives (MGA). This paper provides a stochastic biologically-inspired metaheuristic simulation-optimization MGA method that can efficiently create multiple solution alternatives to problems containing significant stochastic uncertainties that satisfy required system performance criteria and yet are maximally different in their decision spaces. The efficacy of this stochastic MGA approach is demonstrated on a municipal solid waste case study. It is shown that this new computationally efficient algorithmic approach can simultaneously produce the desired number of maximally different solution alternatives in a single computational run of the procedure. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">A VEHICLE ROUTING PROBLEM WITH A PREDEFINED CUSTOMER SEQUENCE, STOCHASTIC DEMANDS AND PENALTIES FOR UNSATISFIED DEMANDS <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">E.G. <span class="SpellE">Kyriakidis</span> and T.D. <span class="SpellE">Dimitrakos</span><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Department of Statistics, Athens University of Economics and Business, Greece </span><span style="font-size: 9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Department of Mathematics, University of the Aegean, <span class="SpellE">Karlovassi</span>, Samos, Greece </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> We consider a stochastic vehicle routing problem in which the customers are served according to a predefined sequence and the demands of the customers are discrete random variables. It is assumed that a penalty cost is imposed if a customer s demand is not satisfied or if it is satisfied partially. The objective is the determination of the policy that serves the customers with the minimum total expected cost. A suitable dynamic programming algorithm is developed for the determination of the optimal policy. It is proved that the optimal policy has a specific threshold-type structure. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">A CONSTRUCTIVE HEURISTIC FOR PERMUTATION FLOW-SHOP SCHEDULING WITH THE MAKESPAN CRITERION: IN A PARTICULAR CASE WHERE THE SUM OF THE PROCESSING TIMES OF EACH JOB IS THE SAME ON EACH MACHINE <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Kaveh Sheibani <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Tadbir Operational Research Group, Vancouver, BC Canada </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> This paper describes an adaption of the fuzzy greedy heuristic (FGH) for the permutation flow-shop scheduling problem with the <span class="SpellE">makespan</span> criterion. In a particular case where the sum of the processing times of each job is the same on each machine, certain priority rule-based scheduling heuristics would assign the same priority to every job, and so in this situation, all possible permutations of the jobs would be equally likely to be selected by those heuristics. An efficient ranking method is proposed to prioritize the jobs in this particular case. Computational experiments using standard benchmark problems indicate that the proposed method is very efficient. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">MODELING AND SOLVING A TIMETABLING PROBLEM CONSIDERING TIME WINDOWS AND CONSECUTIVE PERIODS <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Diana <span class="SpellE">Sánchez-Partida</span>, José Luis <span class="SpellE">Martínez</span>-Flores and Elias Olivares-<span class="SpellE">Benítez</span> <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">UPAEP University, Puebla, México </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> This paper presents a case study called UPAEP Timetabling. This problem arises in the allocation design of some or all of professors-courses-rooms-timeslots-groups variables, considering factors such as availability and capacity rooms. In the reviewed papers a general model that covers the requirements of any Institution have not been found due to operational rules set are determinants for constraints modeled; therefore normally a mathematical model is designed for each Institution. The proposed model is considered one of the most complete due to the kind of considerations in the moment of building the constraints. The model was validated at UPAEP University in the graduate education area, attempting to tackle a real-world problem, considering 85,223 variables, time windows of the professors, periods consecutive and capacity rooms, between other constraints. This document presents a mathematical model solved with commercial optimization software, which helped to found successfully the solution of the Timetabling Problem. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">ON THE USE OF EXPERT OPINION TO CHARACTERISE THE JOINT BEHAVIOUR OF COMPETING RISKS IN INDUSTRIAL ACCELERATED LIFE TESTING <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Herbert Hove <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">School of Statistics and Actuarial Science, University of the Witwatersrand, Johannesburg, South Africa </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> Distribution <span class="SpellE">identifiability</span> issues arise quite naturally through competing risks in reliability. In particular, modeling and analysis of recurrent events which include the impact maintenance has on the lifetime distribution of repairable systems is an interesting practical application. This paper discusses the problem of modeling the joint <span class="SpellE">behaviour</span> of condition-based preventive maintenance (PM) and corrective maintenance (CM) in the competing risk context using copulas. Specifically, how expert <span class="SpellE">judgement</span> and accelerated life testing data can be used to estimate the copula dependence parameter and quantify its uncertainty through Monte-Carlo simulations is discussed. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">AN <span class="GramE"><span style="mso-bidi-font-style:italic">O</span>(</span><span style="mso-bidi-font-style:italic">T </span>3) ALGORITHM FOR THE CAPACITATED ECONOMIC LOT-SIZING PROBLEM WITH STATIONARY CAPACITIES AND CONCAVE COST FUNCTIONS WITH NON-SPECULATIVE MOTIVES <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Pedro <span class="SpellE">Piñeyro</span>, Omar <span class="SpellE">Viera</span> and <span class="SpellE">Héctor</span> <span class="SpellE">Cancela</span> <o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext;mso-bidi-font-style:italic">Instituto</span></span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext; mso-bidi-font-style:italic"> de <span class="SpellE">Computación</span>, <span class="SpellE">Facultad</span> de <span class="SpellE">Ingeniería</span>, Universidad de la <span class="SpellE">República</span>, Montevideo, Uruguay </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> We consider the capacitated economic lot-sizing problem (CLSP) with stationary capacities and concave cost functions with non-speculative motives. Under these assumptions we show that there is an optimal solution of the problem that is composed only by <span class="SpellE">subplans</span> that can be computed in linear time, which means that the problem can be solved in <span style="mso-bidi-font-style:italic">O</span>(<span style="mso-bidi-font-style:italic">T</span> 3) computation time. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">MODELING SCHEDULED PATIENT PUNCTUALITY IN AN INFUSION CENTER <o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext">Seunggyun</span></span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"> Cheong, Robert R. <span class="SpellE">Bitmead</span> and John <span class="SpellE">Fontanesi</span><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Australian Centre for Field Robotics, School of Aerospace, Mechanical and <span class="SpellE">Mechatronic</span> Engineering, the University of Sydney, Australia </span><span style="font-size: 9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Department of Mechanical &amp; Aerospace Engineering, University of California, San Diego, La Jolla CA, USA </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Center for Management Science in Health, University of California, San Diego, La Jolla CA, USA </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> We introduce a new model structure for punctuality of scheduled patients. Each iteration of the model is a mixture of two exponential distributions, one for the punctuality of early-arriving patients and the other for late-arriving patients. Since patients earliness and lateness are treated separately, the models can capture different characteristics of each while many other model structures such as normal distributions treat them symmetrically. The new model structure is tested on data collected in a hospital infusion room and demonstrates quantifiably better performance than normal distribution fitting. The approaches are compared using two goodness-of-fit measures. Further, patient punctuality is shown to vary throughout a day depending on patients appointment times. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">CLUSTERING OF CHARACTERISTICS OVER SPATIAL DATA<o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext">María</span></span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"> Beatriz <span class="SpellE">Bernábe</span> <span class="SpellE">Loranca</span>, Rogelio <span class="SpellE">González</span> Velázquez, <span class="SpellE">Elías</span> Olivares Benitez, David Pinto <span class="SpellE">Avendaño</span>, José Luis <span class="SpellE">Martínez</span> Flores and J R <span class="SpellE">Vanoye</span><o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext;mso-bidi-font-style:italic">Benemérita</span></span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext; mso-bidi-font-style:italic"> Universidad <span class="SpellE">Autónoma</span> de Puebla, <span class="SpellE">Facultad</span> de <span class="SpellE">Ciencias</span> de la <span class="SpellE">Computación</span> Puebla, México </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Universidad Popular <span class="SpellE">Autónoma</span> del Estado de Puebla, <span class="SpellE">Posgrado</span> de <span class="SpellE">Logística</span> y <span class="SpellE">Dirección</span> de la <span class="SpellE">cadena</span> de <span class="SpellE">Suministro</span>, México </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> For problems that require a spatial data analysis, the use of statistical methods that take into account the geographical location or work with the descriptive characteristics of the data in the aggregation process is frequent. To solve a clustering problem over population data, considering the quantitative values of the variables that describe the data is necessary. In these cases, it is assumed that said variables have a high correlation, which suggests a statistical analysis with the goal to achieve a consistent subset of these variables. Even when we count with a subset of variables without redundancies and due to fact that specific problems of population character demand a reduced number of variables, a procedure of data selection under criteria boundaries is important; in this way achieving a subset of variables that describe a specific population problem is possible. Two objects are generated from this procedure: an associated distances matrix formed with the chosen variables and a vector of census-descriptive variables, which are processed by a partitioning algorithm with homogeneity restrictions for a population variable of interest. The homogeneity in the clustering of <span class="SpellE">Agebs</span> (Basic Geo-statistical Areas) is very useful due to the fact that balanced groups are wanted, with respect to a value of a census variable that responds to a population problem. The objective of this work resides in solving the spatial partitioning problem for geographic data under homogeneity restrictions where the variables to consider are directly related with the censuses in Mexico. The <span class="SpellE">Agebs</span> have a geographical composition of latitude-longitude and a vector of 167 descriptive variables of census kind. The partitioning problem is of combinatory character, such that the use of Variable Neighborhood Search (VNS) has been necessary to optimize the objective function with the associated homogeneity restriction. Finally the results are presented for a homogeneous grouping case for economically inactive population. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Supply chain design and sustainability in the textile sector <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">R. <span class="SpellE">Montemanni</span>, C. <span class="SpellE">Valeri</span>, S. <span class="SpellE">Nesic</span>, L.M. Gambardella, M. <span class="SpellE">Gioacchini</span>, T. <span class="SpellE">Fumagalli</span>, H. Zeller, K. Meyer, M. <span class="SpellE">Faist</span> and A.E. Rizzoli<o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">IDSIA  USI/SUPSI, Galleria 2, <span class="SpellE">Manno</span>, Switzerland </span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Hugo Boss Ticino SA, Via S. <span class="SpellE">Apollonia</span> 32, <span class="SpellE">Coldrerio</span>, Switzerland </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">EMPA, <span class="SpellE">Ueberlandstrass</span> 129, <span class="SpellE">Duebendorf</span>, Switzerland </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> A project where optimization techniques and life cycle assessment methods are used to select a supply chain balancing economical and ecological factors is described. In particular, the optimization component will be <span class="SpellE">analysed</span>, <span class="SpellE">modelled</span> in mathematical terms and solved with methods previously appeared in the literature. The supply chain considered is the one of a top-brand firm in the textile sector. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">A CUSTOMER SATISFACTION MODEL BASED ON FUZZY TOPSIS AND SERVQUAL METHODS <o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext">Melike</span></span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"> <span class="SpellE">Erdoan</span>, <span class="SpellE">Özge</span> <span class="SpellE">Nalan</span> <span class="SpellE">Bili_ik</span>, <span class="SpellE">0hsan</span> <span class="SpellE">Kaya</span> and <span class="SpellE">Hayri</span> <span class="SpellE">Baraçl1</span> <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Department of Industrial Engineering, <span class="SpellE">Yildiz</span> Technical University, Istanbul, Turkey </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> Service quality is one of the most important factors that increases the use of public transportation system (PTS). Many problems such as traffic congestion, air and noise pollution, and energy consumption can be solved by improvements of service quality in PTS. In this paper, a hybrid methodology which consists of SERVQUAL (Service Quality) method that categorizes evaluation criteria and fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method that ranks alternatives is suggested for evaluation of service quality in PTS. The suggested methodology is applied in a real case that analyzes the PTS in Istanbul. As a result, the public transportation company that provides the highest customer satisfaction is identified. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">A DYNAMIC PROGRAMMING APPROACH FOR PASSIVE OPTICAL NETWORK DESIGN IN TREE GRAPHS <o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext">Matthieu</span></span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"> <span class="SpellE">Chardy</span>, <span class="SpellE">Cédric</span> <span class="SpellE">Hervet</span> and <span class="SpellE">Dedy</span> <span class="SpellE">Bossia</span><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Orange Labs, <span class="SpellE">Issy</span>-Les-<span class="SpellE">Moulineaux</span>, France </span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">ENSTA/CEDRIC  Orange Labs, <span class="SpellE">Issy</span>-Les-<span class="SpellE">Moulineaux</span>, France </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext;mso-bidi-font-style:italic">Institut</span></span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext; mso-bidi-font-style:italic"> <span class="SpellE">Galilée</span>  <span class="SpellE">Université</span> Paris 13, <span class="SpellE">Villetaneuse</span>, France </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> The deployment of Fiber To The Home technologies is currently one of the most challenging issues for telecommunication operators. This paper focuses on the optimization of Passive Optical Network in tree graphs for which a dynamic programming solving approach is proposed. Tests performed on real-size instances prove the efficiency of this approach in comparison to integer linear programming based approaches. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">AN ACCELERATION OF THE ALGORITHM FOR THE NURSE REROSTERING PROBLEM ON A GRAPHICS PROCESSING UNIT <o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext">Zdenk</span></span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"> <span class="SpellE">Bäumelt</span>, Jan <span class="SpellE">DvoYák</span>, <span class="SpellE">PYemysl</span> <span class="SpellE">`ocha</span> and <span class="SpellE">Zdenk</span> <span class="SpellE">Hanzálek</span> <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Department of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague, <span class="SpellE">Technicka</span> 2, 166 27, Prague 6, Czech Republic </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> This paper deals with the Nurse <span class="SpellE">Rerostering</span> Problem (NRRP) performed by a parallel algorithm on a Graphics Processing Unit (GPU). This problem is focused on rescheduling of human resources in healthcare, when a roster is disrupted by unexpected circumstances. Our aim is to resolve NRRP in a parallel way to shorten the needed computational time in comparison to already known algorithms. The design of the parallel algorithm is a non-trivial task and brings many crucial issues that are described in this paper, e.g. a thread mapping issue, the utilization of the memory and the minimization of the communication overhead between the PC and the GPU. These issues must be taken into account in order to achieve the expected speedup. Our algorithm is evaluated on the benchmark datasets and compared to the optimal results given by ILP. The part of the heterogeneous parallel algorithm running on the GPU was up to 6 times faster in comparison to its sequential version. In total, our parallel algorithm provides a speedup of 1.9 (2.5) times for the NRRP instances with 19 (32) nurses in comparison to the sequential algorithm. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">ANALYZING THE BENEFITS OF MANURE SEPARATION USING MATHEMATICAL OPTIMIZATION <o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext">Hongbo</span></span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"> Dong, Michael Ferris, Tom Cox and John Norman <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">University of Wisconsin-Madison, Madison, USA </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> Optimization techniques are used extensively for strategic and operations planning in a large number of system engineering applications. We consider here the coupling of a crop planning, manure separation process and a nutrient management system for dairy farms. A nonlinear programming model is developed that determines optimal settings for each of these systems when coupled via a parametric herd size and farm layout. The model is at a full farm, or small farm system level. Numerical experiments are provided to illustrate the use of the model for exploring the interactions between environmental constraints and nutrient requirements and the logistic tradeoffs between manure processing and exogenous fertilization. Our results clearly show the benefits of manure separation in both of an environmental metric and an economic metric. Extensions that incorporate coupling of multiple optimization models are also discussed. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">TOWARD CONSTRUCTING AN EFFECTIVE METHOD TO PREDICT OIL PRICES <o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext">Mamoon</span></span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"> <span class="SpellE">Alameen</span>, Mohammed Abdul-<span class="SpellE">Niby</span> and Ali <span class="SpellE">Radhi</span><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Australian College of Kuwait, West <span class="SpellE">Mishrif</span>, Kuwait </span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext;mso-bidi-font-style:italic">Bahbahani</span></span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext; mso-bidi-font-style:italic"> Projects, Kuwait city, Kuwait </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> As human civilizations advance, the dependence on oil grows rapidly. Predicting oil prices is a big challenge due to the importance of oil in effecting human life style. Unlike any other commodity, oil prices can t be left to supply and demand factor only. The most popular approach to predict future oil prices is the statistical approach. The purpose of this study is to investigate the validity of taking a non statistical approach to predict oil prices. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">SCHEDULING OF TRUCKS IN CROSS-DOCKING SYSTEMS: A HYBRID META-HEURISTIC ALGORITHM <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">B. <span class="SpellE">Vahdani</span>, R. <span class="SpellE">Tavakkoli-Moghaddam</span>, and S.M. <span class="SpellE">Mousavi</span> <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> Cross-docking is a logistics technique that minimizes the storage and order picking functions of a warehouse while still allowing it to serve its receiving and shipping functions. In this paper, we propose a novel hybrid meta-heuristic algorithm for solving scheduling trucks in cross-docking problems. This algorithm comprises three components: an initial population generation method based on ant colony optimization (ACO), simulated annealing (SA) as an evolutionary algorithm employs a certain probability to avoid becoming trapped in local optimum, and variable neighborhood search (VNS) that involves three local search procedures to improve the population. Moreover, to demonstrate the effectiveness of the proposed methods especially for large-sized problems, various test problems are solved. The computational results demonstrate that our proposed algorithm performs far better than those of Yu and <span class="SpellE">Egbelu</span> (2008). <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">A HYBRID GA FOR SIMULTANEOUSLY SCHEDULING AN FMC UNDER MULTIPLE OBJECTIVES <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">R. <span class="SpellE">Tavakkoli-Moghaddam</span>, M. <span class="SpellE">Heydar</span> and S.M. <span class="SpellE">Mousavi</span><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">School of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Department of Industrial and Manufacturing Engineering, University of Wisconsin, Milwaukee, USA </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Young Researches Club, South Tehran Branch, Islamic Azad University, Tehran, Iran </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> This paper solved a bi-objective scheduling problem in flexible manufacturing cell. The objectives considered are maximum completion time (<span class="SpellE">makespan</span>) and maximum tardiness. This class of scheduling problem, regardless of the criterion, belongs to the class of NP-hard problems. Therefore, exact methods are not able to solve practical cases of these types of problems. For this research, a new hybrid genetic algorithm (HGA) combined with four priority dispatching rules is proposed. For numerical study purposes different scheduling problems are generated and solved using the proposed HGA. The results show that the proposed approach performs well in terms of efficiency and quality of the solutions. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">A SAMPLING-BASED APPROXIMATION OF THE OBJECTIVE FUNCTION OF THE ORIENTEERING PROBLEM WITH STOCHASTIC TRAVEL AND SERVICE TIMES <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">V. <span class="SpellE">Papapanagiotou</span>, D. <span class="SpellE">Weyland</span>, R. <span class="SpellE">Montemanni</span> and L.M. Gambardella <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">IDSIA  USI/SUPSI, Galleria 2, <span class="SpellE">Manno</span>, Switzerland </span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> In this paper, a variant of the orienteering problem in which the travel and service times are stochastic, is examined. Given a set of potential customers, a subset of them has to be selected to be serviced by the end of the day. Every time a delivery to a selected customer is fulfilled before the end of the day, a reward is received, otherwise, if the delivery is not completed, a penalty is incurred. The target is to <span class="SpellE">maximise</span> the expected income (rewards-penalties) of the company. The focus of this paper is to evaluate a sampling based way to approximate the objective function which is designed to be later embedded in metaheuristics. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">SCHEDULING ELECTIVE PATIENT ADMISSIONS CONSIDERING ROOM ASSIGNMENT AND OPERATING THEATRE CAPACITY CONSTRAINTS <o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext">Wim</span></span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"> <span class="SpellE">Vancroonenburg</span>, Patrick De <span class="SpellE">Causmaecker</span>, Frits <span class="SpellE">Spieksma</span> and Greet <span class="SpellE">Vanden</span> <span class="SpellE">Berghe</span><o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext;mso-bidi-font-style:italic">CODeS</span></span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext; mso-bidi-font-style:italic">, KAHO <span class="SpellE">Sint-Lieven</span>, Gent, Belgium </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext"><o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext;mso-bidi-font-style:italic">CODeS</span></span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext; mso-bidi-font-style:italic">, KU Leuven KULAK, Kortrijk, Belgium </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">ORSTAT, Faculty of Economics and Business, KU Leuven, Leuven, Belgium </span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> The present contribution studies an elective patient admission scheduling problem considering both operating theatre capacity and room assignment constraints. The aim of the study is to determine how scheduling surgical and non-surgical admissions impacts room assignment issues at hospital wards, and how these can be avoided. We present a problem setting and the corresponding mathematical formulation as the basis of our study. First results will be presented at the conference. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">A VARIABLE NEIGHBORHOOD SEARCH FOR THE SELECTIVE MULTI-COMPARTMENT VEHICLE ROUTING PROBLEM WITH TIME WINDOWS <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Jan <span class="SpellE">Melechovský</span> <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">University of Economics, Prague, Department of Econometrics, Prague, Czech Republic </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> This paper presents a generalization of the well-known vehicle routing problem with time windows (VRPTW). In the proposed selective multi-compartment VRPTW (SMCVRPTW) a limited number <span style="mso-bidi-font-style:italic">k</span> of <span class="SpellE">identic</span> vehicles is available at a central depot to serve a set of customers. Each vehicle is equipped with m compartments of limited capacity which are dedicated to transport a particular type of a product. Each customer has a nonnegative demand for up to m products. Once a vehicle delivers a product p to a customer it collects a profit. A vehicle can visit a customer only within a given time window. The SMCVRPTW consist of determining a set of at most k routes starting and ending at the depot, satisfying all customer requests under capacity and time windows constraints such that the total collected profit is maximized. We present a variable neighborhood search algorithm to address the problem. The solution method is evaluated on standard VRPTW benchmarks enhanced with compartments and profit values. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">IT'S TIME FOR A CHANGE TO BETTER UTILIZE RESOURCES IN HEALTHCARE <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Tomas Eric <span class="SpellE">Nordlander</span>, Greet <span class="SpellE">Vanden</span> <span class="SpellE">Berghe</span> and Patrick <span class="SpellE">Schittekat</span><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">SINTEF ICT, Department of Applied Mathematics, Oslo, Norway </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext"><o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext;mso-bidi-font-style:italic">CODeS</span></span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext; mso-bidi-font-style:italic">, KAHO, Gent, Belgium </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext;mso-bidi-font-style:italic">iMinds</span></span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext; mso-bidi-font-style:italic">-ITEC-KU Leuven, Belgium </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> To manage the rapid increase of hospital patients, there is an immediate need to improve efficiency of resource <span class="SpellE">utilisation</span> in healthcare. Adopting and applying traditional Operational Research techniques such as optimization is probably the most potent instrument to do this. However, to create a significant impact we need to dissolve the traditional problem partitions  formed by the limitation in processing power, outdated methods, and manual practice. Over the years, a substantial increase in processing power with significant improved methods has taken place. Still, the old partitions remain. We argue that it is high time to move to a more efficient partition that supports a better resource <span class="SpellE">utilisation</span>. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">INTEGRATED PROJECT CONTROLS: USING OPERATIONS RESEARCH METHODS TO IMPROVE THE EFFICIENCY OF PROJECT CONTROL <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Mario <span class="SpellE">Vanhoucke</span> <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Ghent University, Ghent, Belgium </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span class="SpellE"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext;mso-bidi-font-style:italic">Vlerick</span></span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext; mso-bidi-font-style:italic"> Business School, Belgium, Russia and China - and University College London, UK </span><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Partner OR-AS (Operations Research - Applications and Solutions) </span><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> Baseline scheduling and risk analysis go hand in hand and are crucial preparatory dimensions to provide information for the project control phase. One of the central lessons in training sessions to project managers is that scheduling without any form of risk management makes no sense since it then boils down to an academic and deterministic optimization exercise without much real life value. A project schedule is a dynamic instrument that needs to be adapted when necessary. Project managers have to deal with a continuous stream of unexpected events and need to take corrective actions to bring projects back on track or to update the initial estimates and expectations to a more realistic scenario. In that respect, a dynamic project schedule is the ideal tool to provide information and to support the corrective actions, and hence, the project baseline schedule acts as a point-of-reference to support these actions, rather than a forecast of the future that needs to be followed at all times. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">PERFORMANCE ANALYSIS OF INVESTMENT STRATEGIES  PITFALLS AND SURPRISES <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Peter <span class="SpellE">Scholz</span> and Ursula Walther<o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Hamburg School of Business Administration, Hamburg, Germany </span><span style="font-size:9.0pt; font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font: major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Berlin School of Economics and Law, Berlin, Germany </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family: Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> Active investment strategies are a subject of endless debates. Myriads of studies have been conducted to proof performance potential - or to reject previous studies due to flaws or misinterpretations. The presentation will address three specific aspects which often are disregarded when performance is measured. Firstly, we will discuss the role of <span class="SpellE">backtests</span> and show that this instrument  even when used carefully and skilled  may lead to biased and misleading results. Secondly, we give an example that the concepts of performance and forecast power must be strictly distinguished. Finally, we demonstrate that implementation details, while largely neglected, may strongly impact and bias a strategy s performance. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">OPTIMAL PORTFOLIO CHOICE WITH MULTIPLE BENCHMARKS<o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Jan <span class="SpellE">Vecer</span> <o:p></o:p></span></p> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext;mso-bidi-font-style:italic">Frankfurt School of Finance and Management, Frankfurt, Germany</span><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></p> <p><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family: &quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin; mso-bidi-font-family:Arial;color:windowtext"> The objective of many portfolio managers is to beat a specific benchmark. This benchmark is typically chosen to be the stock market. The performance of the fund is then compared with a performance of the benchmark, say a stock index SP500 for a fund that invest in US stocks. From the no arbitrage arguments, it is impossible to beat the stock index for sure, thus such an investment strategy can guarantee success only with a certain probability. The problem how to maximize the probability of beating a specific index by a certain percentage has already been widely studied in the previous literature. Thus we focus our attention to another drawback of such a strategy. The fund manager can still beat the stock index, but in the situation of a market downturn, his strategy can significantly underperform the money market, making the investor worse off in comparison to a conservative strategy of holding the currency. We can formulate the investment problem in the following way: we want the investment fund <span style="mso-bidi-font-style:italic">X</span> to have at least <span style="mso-bidi-font-style:italic">a</span> units of the stock market <span style="mso-bidi-font-style:italic">S</span> and at least <span style="mso-bidi-font-style:italic">b</span> units of the money market <span style="mso-bidi-font-style:italic">M</span> at the end of the monitoring period <span style="mso-bidi-font-style:italic">T</span>. Thus the objective is <span style="mso-bidi-font-style:italic">X_T &gt; max(a S_T, b M_T). </span>There is a region of values <span style="mso-bidi-font-style:italic">a</span> and <span style="mso-bidi-font-style:italic">b</span> such that this objective can be satisfied for sure and we find his set of feasible values in the geometric Brownian motion model. Certainly any values above 1 for both <span style="mso-bidi-font-style:italic">a </span>and <span style="mso-bidi-font-style: italic">b</span> are not feasible, this would create an arbitrage opportunity. We also find the trading strategy that would deliver the objective portfolio for any <span class="SpellE"><span style="mso-bidi-font-style:italic">a</span></span> and <span style="mso-bidi-font-style:italic">b</span> in the feasible set. Since both values of <span style="mso-bidi-font-style:italic">a</span> and <span style="mso-bidi-font-style:italic">b</span> must be below 1, there is a possibility that the resulting portfolio would underperform both the stock and the money market. We explicitly compute this probability. As it turns out, this probability of underperformance of both benchmarks converges to zero as time goes to infinity. For the values of <span style="mso-bidi-font-style:italic">a</span> and <span style="mso-bidi-font-style:italic">b</span> outside of the feasible set, we can find the investment strategy that beats both benchmarks with the largest probability. In particular, we solve for the case <span style="mso-bidi-font-style:italic">a=b=1</span>, which delivers the better of the two benchmarks. In the remaining part of the paper, we solve the problem of optimal investment for an arbitrary number of benchmarks, which can be for instance applied to foreign exchange markets. <o:p></o:p></span></p> <div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;; mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;; mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> <hr size="2" width="100%" noshade style="color:#A0A0A0" align="left"> </span></div> <p><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font: major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial; color:windowtext">© ORLab Analytics Inc.<o:p></o:p></span></p> </div> </div> </body> </html> <!-- FILE ARCHIVED ON 15:10:21 Jul 12, 2020 AND RETRIEVED FROM THE INTERNET ARCHIVE ON 15:04:27 Feb 26, 2022. JAVASCRIPT APPENDED BY WAYBACK MACHINE, COPYRIGHT INTERNET ARCHIVE. ALL OTHER CONTENT MAY ALSO BE PROTECTED BY COPYRIGHT (17 U.S.C. SECTION 108(a)(3)). --> <!-- playback timings (ms): captures_list: 552.293 exclusion.robots: 0.096 exclusion.robots.policy: 0.088 RedisCDXSource: 4.274 esindex: 0.009 LoadShardBlock: 531.771 (3) PetaboxLoader3.datanode: 62.077 (4) CDXLines.iter: 13.789 (3) PetaboxLoader3.resolve: 509.74 (2) load_resource: 76.939 -->