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Radiotherapy treatment scheduling considering time window preferences

Author

Listed:
  • Bruno Vieira

    (Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital
    University of Twente)

  • Derya Demirtas

    (University of Twente
    University of Twente)

  • Jeroen B. Kamer

    (Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital)

  • Erwin W. Hans

    (University of Twente
    University of Twente)

  • Louis-Martin Rousseau

    (Polytechnique Montreal)

  • Nadia Lahrichi

    (Polytechnique Montreal)

  • Wim H. Harten

    (Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital
    Rijnstate General Hospital)

Abstract

External-beam radiotherapy treatments are delivered by a linear accelerator (linac) in a series of high-energy radiation sessions over multiple days. With the increase in the incidence of cancer and the use of radiotherapy (RT), the problem of automatically scheduling RT sessions while satisfying patient preferences regarding the time of their appointments becomes increasingly relevant. While most literature focuses on timeliness of treatments, several Dutch RT centers have expressed their need to include patient preferences when scheduling appointments for irradiation sessions. In this study, we propose a mixed-integer linear programming (MILP) model that solves the problem of scheduling and sequencing RT sessions considering time window preferences given by patients. The MILP model alone is able to solve the problem to optimality, scheduling all sessions within the desired window, in reasonable time for small size instances up to 66 patients and 2 linacs per week. For larger centers, we propose a heuristic method that pre-assigns patients to linacs to decompose the problem in subproblems (clusters of linacs) before using the MILP model to solve the subproblems to optimality in a sequential manner. We test our methodology using real-world data from a large Dutch RT center (8 linacs). Results show that, combining the heuristic with the MILP model, the problem can be solved in reasonable computation time with as few as 2.8% of the sessions being scheduled outside the desired time window.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:hcarem:v:23:y:2020:i:4:d:10.1007_s10729-020-09510-8
    DOI: 10.1007/s10729-020-09510-8
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    References listed on IDEAS

    as
    1. 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.
    2. Coelho, José & Vanhoucke, Mario, 2011. "Multi-mode resource-constrained project scheduling using RCPSP and SAT solvers," European Journal of Operational Research, Elsevier, vol. 213(1), pages 73-82, August.
    3. Vieira, Bruno & Demirtas, Derya & van de Kamer, Jeroen B. & Hans, Erwin W. & van Harten, Wim, 2018. "A mathematical programming model for optimizing the staff allocation in radiotherapy under uncertain demand," European Journal of Operational Research, Elsevier, vol. 270(2), pages 709-722.
    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 & 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.

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