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.

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)

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.