Combined mathematical programming and heuristics for a radiotherapy pre-treatment scheduling problem

Authors:
Elkin Castro;Sanja Petrovic
Affiliations:
Automated Scheduling, Optimisation and Planning (ASAP) Research Group, School of Computer Science, University of Nottingham, Nottingham, UK NG8 1BB;Automated Scheduling, Optimisation and Planning (ASAP) Research Group, School of Computer Science, University of Nottingham, Nottingham, UK NG8 1BB
Venue:
Journal of Scheduling
Year:
2012

Citing 3
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Abstract

Demand for radiotherapy treatment services has increased due to higher cancer incidence, ageing population, and a larger number of prescribed radiotherapy fractions. This higher demand can, in turn, produce longer waiting times for radiotherapy treatment. We introduce a real-world radiotherapy pre-treatment scheduling problem at a hospital in the UK. This scheduling problem is modelled as an optimisation problem with multiple objectives. The objectives are hierarchical, thus the solution approach is based on solving a series of single-objective optimisation scheduling problems. Each of these problems is formulated as a mathematical programming model. Dispatching rules were introduced to produce an initial solution for the mathematical programming model. Their performance is compared to the mathematical programming approach.