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A two-phase approach for the Radiotherapy Scheduling Problem

Author

Listed:
  • Tu-San Pham

    (Polytechnique Montréal)

  • Louis-Martin Rousseau

    (Polytechnique Montréal)

  • Patrick Causmaecker

    (KU Leuven)

Abstract

The Radiotherapy Scheduling Problem (RTSP) focuses on optimizing the planning of radiotherapy treatment sessions for cancer patients. In this paper, we propose a two-phase approach for the RTSP. In the first phase, radiotherapy sessions are assigned to specific linear accelerators (linacs) and days. The second phase then decides the sequence of patients on each day/linac and the specific appointment times. For the first phase, an Integer Linear Programming (IP) model is proposed and solved using CPLEX. For the second phase, a Mixed Integer Linear Programming (MIP) and a Constraint Programming (CP) model are proposed. The test data is generated based on real data from CHUM, a large cancer center in Montréal, Canada, with an average of 3,500 new patients and 40,000 radiotherapy treatments per year. The results show that in the second phase, CP is better at finding good solutions quickly while MIP is better at closing optimality gaps with more run time. Lastly, a simulation is conducted to evaluate the impact of different scheduling strategies on the outcome of the scheduling. Preliminary results show that batch scheduling reduces patients’ waiting time and overdue time.

Suggested Citation

  • Tu-San Pham & Louis-Martin Rousseau & Patrick Causmaecker, 2022. "A two-phase approach for the Radiotherapy Scheduling Problem," Health Care Management Science, Springer, vol. 25(2), pages 191-207, June.
    • Handle: RePEc:kap:hcarem:v:25:y:2022:i:2:d:10.1007_s10729-021-09579-9
    DOI: 10.1007/s10729-021-09579-9
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    References listed on IDEAS

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    1. Bruno Vieira & Derya Demirtas & Jeroen B. Kamer & Erwin W. Hans & Louis-Martin Rousseau & Nadia Lahrichi & Wim H. Harten, 2020. "Radiotherapy treatment scheduling considering time window preferences," Health Care Management Science, Springer, vol. 23(4), pages 520-534, December.
    2. Petra Vogl & Roland Braune & Karl F. Doerner, 2019. "Scheduling recurring radiotherapy appointments in an ion beam facility," Journal of Scheduling, Springer, vol. 22(2), pages 137-154, April.
    3. Yasin Gocgun, 2018. "Simulation-based approximate policy iteration for dynamic patient scheduling for radiation therapy," Health Care Management Science, Springer, vol. 21(3), pages 317-325, September.
    4. Conforti, D. & Guerriero, F. & Guido, R., 2010. "Non-block scheduling with priority for radiotherapy treatments," European Journal of Operational Research, Elsevier, vol. 201(1), pages 289-296, February.
    5. Sauré, Antoine & Patrick, Jonathan & Tyldesley, Scott & Puterman, Martin L., 2012. "Dynamic multi-appointment patient scheduling for radiation therapy," European Journal of Operational Research, Elsevier, vol. 223(2), pages 573-584.
    6. Antoine Legrain & Marie-Andrée Fortin & Nadia Lahrichi & Louis-Martin Rousseau, 2015. "Online stochastic optimization of radiotherapy patient scheduling," Health Care Management Science, Springer, vol. 18(2), pages 110-123, June.
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    Cited by:

    1. Tu San Pham & Antoine Legrain & Patrick De Causmaecker & Louis-Martin Rousseau, 2023. "A Prediction-Based Approach for Online Dynamic Appointment Scheduling: A Case Study in Radiotherapy Treatment," INFORMS Journal on Computing, INFORMS, vol. 35(4), pages 844-868, July.

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