Contributions to Proceedings:
J. Maschler, M. Riedler, G. Raidl:
"Particle Therapy Patient Scheduling: Time Estimation for Scheduling Sets of Treatments";
in: "Computer Aided Systems Theory - EUROCAST 2017",
issued by: Springer Verlag;
Springer,
2018,
ISBN: 978-3-319-74717-0,
364
- 372.
English 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.
Keywords:
Particle therapy patient scheduling Time estimation Bilevel optimization Surrogate objective function Iterated greedy metaheuristic
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.1007/978-3-319-74718-7_44
Electronic version of the publication:
https://publik.tuwien.ac.at/files/publik_273743.pdf
Created from the Publication Database of the Vienna University of Technology.