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Branch-and-check methods for multi-level operating room planning and scheduling

机译:多层手术室计划和调度的分支检查方法

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We develop the first exact decomposition approaches for a multi-level operating room planning and scheduling problem that integrates case mix planning, master surgical scheduling, and surgery sequencing in the presence of multiple surgical specialties. Our approaches consist of novel uni-level and bi-level branch-and-check algorithms that solve the problem using a hybridization of integer programming and constraint programming. We demonstrate that our approaches outperform an existing time-indexed integer programming model, yielding significant improvements on solution quality. Our methods are competitive with an existing genetic algorithm while providing provable bounds on solution quality. We conduct an investigation into the impact of time discretization on our algorithms, illustrating that our decompositions, unlike the previously proposed integer programming approach, are much less sensitive to time discretization and produce more accurate solutions as a result. Finally, we introduce and investigate benchmark instances with a more diverse case mix. Overall, we conclude that our decompositions are the most appropriate approaches for this multi-level operating room planning and scheduling problem.
机译:我们针对多级手术室计划和排程问题开发了第一种精确分解方法,该方法将病案混合计划,主手术排程和手术顺序集成到多个手术专科中。我们的方法由新颖的单级和双层分支和检查算法组成,这些算法使用整数规划和约束规划的混合来解决问题。我们证明了我们的方法优于现有的时间索引整数规划模型,从而显着提高了解决方案质量。我们的方法与现有的遗传算法相比具有竞争优势,同时为解决方案质量提供了可证明的界限。我们对时间离散化对算法的影响进行了调查,结果表明,与先前提出的整数编程方法不同,我们的分解对时间离散化的敏感度要低得多,从而可以得出更准确的解。最后,我们介绍和研究具有更多案例组合的基准实例。总的来说,我们得出结论,对于这种多层次的手术室计划和调度问题,分解是最合适的方法。

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