Abstract
This paper presents a multi-objective model for scheduling of radiotherapy treatments for cancer patients based on genetic algorithms (GA). The model is developed and implemented considering real life radiotherapy treatment processes at Arden Cancer Centre, Coventry, UK. Two objectives are defined: minimisation of the Average patient waiting times and minimisation of Average tardiness of the patient first treatment fractions. Two scenarios are analysed considering the availability of the doctors to approve treatment plans. The schedules generated by the GA using real data collected from the collaborating Cancer Centre have good performance. It is demonstrated that enabling doctors to approve treatment plans instantly has a great impact on Average waiting time and Average tardiness for all patient categories.
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References
Pinedo, M.: Scheduling: Theory, Algorithms and Systems. Prentice-Hall, New Jersey (2002)
Conforti, D., Guerriero, F., Guido, R.: Optimisation Models for Radiotherapy Patient Scheduling. 4OR: Quart J. Ops. Res. 6(3), 263–278 (2008)
Kapamara, T., Sheibani, K., Petrovic, D., Haas, O., Reeves, C.R.: A Simulation of a Radiotherapy Treatment Systems: A Case Study of a Local Cancer Centre. In: Proc. of ORP3 Conference, Guimaraes, Portugal, pp. 29–35 (2007)
Larsson, S.N.: Radiotherapy Patient Scheduling Using a Desktop Personal Comp. J. Clini-cal Oncology 5, 98–101 (1993)
Petrovic, S., Leung, W., Song, X., Sundar, S.: Algorithms for Radiotherapy Treatment Booking. In: 25th Workshop of the UK Planning and Scheduling Special Interest Group, Nottingham, UK, pp. 105–112 (2006)
Joint Collegiate Council for Oncology (JCCO). Reducing Delays in Cancer Treatment: Some Targets. Technical report, Royal College of Physicians, London (1993)
Deb, K.: Multiobjective Optimisation using Evolutionary Algorithms. John Wiley & Sons, New York (2001)
Goldberg, D.: Genetic Algorithms in Search, Optimisation & Machine Learning. Addison Wesley, Reading (1989)
Gen, M., Tsujimura, Y., Kubota, E.: Solving Job-shop Scheduling Problems by Genetic Algorithm. In: Proc. IEEE International Conference on Systems, Man, and Cybernetics, Texas, vol. 2, pp. 1577–1582 (1994)
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© 2009 Springer-Verlag Berlin Heidelberg
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Petrovic, D., Morshed, M., Petrovic, S. (2009). Genetic Algorithm Based Scheduling of Radiotherapy Treatments for Cancer Patients. In: Combi, C., Shahar, Y., Abu-Hanna, A. (eds) Artificial Intelligence in Medicine. AIME 2009. Lecture Notes in Computer Science(), vol 5651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02976-9_14
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DOI: https://doi.org/10.1007/978-3-642-02976-9_14
Publisher Name: Springer, Berlin, Heidelberg
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