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Large-scale medical examination scheduling technology based on intelligent optimization

Author

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  • Jiawei Zhang

    (National University of Defense Technology)

  • Ling Wang

    (Tsinghua University)

  • Lining Xing

    (National University of Defense Technology)

Abstract

In recent years, the scale of the health examination business has increased rapidly, and research on the combinatorial optimization of medical examinations has become more important. In this context, a special large-scale flexible open shop scheduling problem (FOSP) is introduced based on the idea of the multi-processor open shop scheduling problem. A mixed integer programming model is developed for the FOSP, which regards client satisfaction as the most important objective. As the FOSP is particularly complex, three different intelligent optimization algorithms are examined, namely a genetic algorithm, hybrid particle swarm optimization, and simulated annealing. According to the medical examination preferences of the clients, a group of large-scale test problems are created on the basis of benchmark instances of the flexible job shop problem, and these are used to evaluate the performance of each algorithm. The experimental results show that the genetic algorithm outperforms both simulated annealing and hybrid particle swarm optimization, especially in large-scale problems.

Suggested Citation

  • Jiawei Zhang & Ling Wang & Lining Xing, 2019. "Large-scale medical examination scheduling technology based on intelligent optimization," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 385-404, January.
    • Handle: RePEc:spr:jcomop:v:37:y:2019:i:1:d:10.1007_s10878-017-0246-6
    DOI: 10.1007/s10878-017-0246-6
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    References listed on IDEAS

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    Cited by:

    1. Xu Tan & Lining Xing & Zhaoquan Cai & Gaige Wang, 2020. "Analysis of production cycle-time distribution with a big-data approach," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 1889-1897, December.
    2. Zeynep Adak & Mahmure Övül Arıoğlu Akan & Serol Bulkan, 0. "Multiprocessor open shop problem: literature review and future directions," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-23.
    3. Zeynep Adak & Mahmure Övül Arıoğlu & Serol Bulkan, 2022. "An ant colony optimization approach for the proportionate multiprocessor open shop," Journal of Combinatorial Optimization, Springer, vol. 43(4), pages 785-817, May.
    4. Agnihothri, Saligrama & Cappanera, Paola & Nonato, Maddalena & Visintin, Filippo, 2024. "Appointment scheduling in surgery pre-admission testing clinics," Omega, Elsevier, vol. 123(C).
    5. Zeynep Adak & Mahmure Övül Arıoğlu Akan & Serol Bulkan, 2020. "Multiprocessor open shop problem: literature review and future directions," Journal of Combinatorial Optimization, Springer, vol. 40(2), pages 547-569, August.

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