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J. Maschler, M. Riedler, G. Raidl:
"Particle Therapy Patient Scheduling: Time Estimation for Scheduling Sets of Treatments";
in: "Computer Aided Systems Theory - EUROCAST 2017", herausgegeben von: Springer Verlag; Springer, 2018, ISBN: 978-3-319-74717-0, S. 364 - 372.

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.

Particle therapy patient scheduling Time estimation Bilevel optimization Surrogate objective function Iterated greedy metaheuristic

http://dx.doi.org/10.1007/978-3-319-74718-7_44

https://publik.tuwien.ac.at/files/publik_273743.pdf