Abstract
In the particle therapy patient scheduling problem (PTPSP) cancer therapies consisting of sequences of treatments have to be planned within a planning horizon of several months. In our previous works we approached PTPSP by decomposing it into a day assignment part and a sequencing part. The decomposition makes the problem more manageable, however, both levels are dependent on a large degree. The aim of this work is to provide and a surrogate objective function that quickly predicts the behavior of the sequencing part with reasonable precision, allowing an improved day assignment w.r.t. the original problem.
We thank EBG MedAustron GmbH, Wiener Neustadt, Austria, for the collaboration on particle therapy patient scheduling and partially funding this work.
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Burke, E.K., Leite-Rocha, P., Petrovic, S.: An integer linear programming model for the radiotherapy treatment scheduling problem. CoRR abs/1103.3391 (2011)
Conforti, D., Guerriero, F., Guido, R.: Optimization models for radiotherapy patient scheduling. 4OR 6(3), 263–278 (2008)
Kapamara, T., Petrovic, D.: A heuristics and steepest hill climbing method to scheduling radiotherapy patients. In: Proceedings of the International Conference on Operational Research Applied to Health Services (ORAHS). Catholic University of Leuven, Leuven, Belgium (2009)
Kapamara, T., Sheibani, K., Haas, O., Petrovic, D., Reeves, C.: A review of scheduling problems in radiotherapy. In: Proceedings of the International Control Systems Engineering Conference (ICSE), pp. 207–211. Coventry University Publishing, Coventry, UK (2006)
Maschler, J., Hackl, T., Riedler, M., Raidl, G.R.: An enhanced iterated greedy metaheuristic for the particle therapy patient scheduling problem. In: Proceedings of the 12th Metaheuristics International Conference. Barcelona, Spain (2017)
Maschler, J., Riedler, M., Stock, M., Raidl, G.R.: Particle therapy patient scheduling: first heuristic approaches. In: Proceedings of the 11th International Conference on the Practice and Theory of Automated Timetabling, pp. 223–244. Udine, Italy (2016)
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, pp. 105–112. Nottingham, UK (2006)
Petrovic, S., Leite-Rocha, P.: Constructive and GRASP approaches to radiotherapy treatment scheduling. In: Advances in Electrical and Electronics Engineering - IAENG Special Edition of the World Congress on Engineering and Computer Science 2008, pp. 192–200. IEEE (2008)
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Maschler, J., Riedler, M., Raidl, G.R. (2018). Particle Therapy Patient Scheduling: Time Estimation for Scheduling Sets of Treatments. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2017. EUROCAST 2017. Lecture Notes in Computer Science(), vol 10671. Springer, Cham. https://doi.org/10.1007/978-3-319-74718-7_44
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DOI: https://doi.org/10.1007/978-3-319-74718-7_44
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