PATIENT SCHEDULING IN RADIOTHERAPY PLANNING

 

S Sheibani, K Sheibani

 

Abstract

 

This paper describes a very fast heuristic for a real-life scheduling problem arising at a major local radiotherapy clinic. After referral to radiotherapy, patients need to visit a set of certain facilities sequentially within a specific due date before starting a treatment scheme. Each patient requires each facility at most once for a roughly determined amount of time. These operations are traditionally recognised as the radiotherapy planning. The main objective is to minimise the mean flow time of the patients in the radiotherapy planning. The problem can be seen as a dynamic job shop environment. The proposed method consists of two phases: building a list of patients and constructing a schedule. A fuzzy greedy evaluation function is employed to prioritise the operations in the list for incorporating into the construction phase of the heuristic. Computational experiments on standard benchmark problems indicate that the proposed method is very effective. Monte Carlo simulation will be also applied to validate the proposed scheduling model.

 

Lecture Notes in Management Science (2011) Vol. 3: 285-288

3rd International Conference on Applied Operational Research, Proceedings

© Tadbir Operational Research Group Ltd. All rights reserved.

www.tadbir.ca

 

ISSN 2008-0050 (Print)

ISSN 1927-0097 (Online)

 

ARTICLE OUTLINE

 

·         Methodology

·         Some Experimental Results

·         Concluding Remarks

 

References

 

1.     Garey MR, Johnson DS and Sethi R (1976). The Complexity of Flowshop and Job-shop Scheduling. Mathematics of Operations Research 1: 117-129.

2.     Kapamara T, Sheibani K, Haas OCL, Reeves CR and Petrovic D (2006). A Review of Scheduling Problems in Radiotherapy. Proceedings of the 18th International Conference on Systems Engineering, Coventry, UK, pp 207-211.

3.     Kapamara T, Sheibani K, Petrovic D, Haas OCL and Reeves CR (2007). A Simulation of a Radiotherapy Treatment System: A Case Study of a Local Cancer Centre. Proceedings of ORP3 Conference, Guimaraes, Portugal, pp 29-35.

4.     Pinson E (1995). The Job Shop Scheduling Problem: A Concise Survey and Some Recent Developments. In: Chretienne P, Coffman Jr EG, Lenstra JK and Liu Z (eds). Scheduling Theory and its Application. John Wiley & Sons: Chichester, England pp 277-293.

5.     Sheibani K (2005). Fuzzy Greedy Evaluation in Search, Optimisation, and Learning. PhD thesis, London Metropolitan University, London, UK.

6.     Sheibani K (2008). Fuzzy Greedy Search in Combinatorial Optimisation. Tadbir Institute for Operational Research, Systems Design and Financial Services: Tehran.

7.     Sheibani K (2010). A fuzzy greedy heuristic for permutation flow-shop scheduling. Journal of the Operational Research Society 61: 813-818.

8.     Taillard E (1993). Benchmarks for Basic Scheduling Problems. European Journal of Operational Research 64: 278-285.

 

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