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Models for Radiation Therapy Patient Scheduling
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.ORCID iD: 0000-0002-6283-7004
2019 (English)In: 25th International Conference on Principles and Practice of Constraint Programming, CP 2019, Springer, 2019, Vol. 11802, p. 421-437Conference paper, Published paper (Refereed)
Abstract [en]

In Europe, around half of all patients diagnosed with cancer are treated with radiation therapy. To reduce waiting times, optimizing the use of linear accelerators for treatment is crucial. This paper introduces an Integer Programming (IP) and two Constraint Programming (CP) models for the non-block radiotherapy patient scheduling problem. Patients are scheduled considering priority, pattern, duration, and start day of their treatment. The models include expected future patient arrivals. Treatment time of the day is included in the models as time windows which enable more realistic objectives and constraints. The models are thoroughly evaluated for multiple different scenarios, altering: planning day, machine availability, arrival rates, patient backlog, and the number of time windows in a day. The results demonstrate that the CP models find feasible solutions earlier, while the IP model reaches optimality considerably faster.

Place, publisher, year, edition, pages
Springer, 2019. Vol. 11802, p. 421-437
Series
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743 ; 11802
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-265123DOI: 10.1007/978-3-030-30048-7_25Scopus ID: 2-s2.0-85075737127ISBN: 9783030300470 (print)OAI: oai:DiVA.org:kth-265123DiVA, id: diva2:1377367
Conference
25th International Conference on Principles and Practice of Constraint Programming, CP 2019; Stamford; United States; 30 September 2019 through 4 October 2019
Note

QC 20191211

Available from: 2019-12-11 Created: 2019-12-11 Last updated: 2020-01-29Bibliographically approved

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Schulte, Christian

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  • apa
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