AI 中文总结
该研究针对周末床位约束下的综合手术排程与病例分配问题，提出联合优化框架，采用列生成算法求解，实验表明其性能优于直接MILP求解，为医院资源平衡提供管理见解。
AI 中文摘要
本文研究了周末床位容量约束下的综合主手术排程问题与手术病例分配问题。我们提出了一种联合优化框架，该框架在考虑周末床位可用性降低的同时，同时确定专科与外科医生对手术室（OR）区块的分配、患者对这些区块的选择与分配，以及手术的排序。该模型被构建为一个多准则混合整数线性规划（MILP），其目标是最大化已排程患者的总优先级加权量、最小化周末床位占用过量，以及最大化手术室利用率。为求解大规模实例，我们开发了一种列生成（CG）算法，其中定价子问题被构建为资源约束最短路径问题。该框架支持区块式、开放式及改良区块式排程策略。计算实验表明，在解的质量和计算时间方面，尤其是对于较大规模的实例，列生成（CG）方法优于直接的混合整数线性规划（MILP）求解。我们进一步分析了周末床位可用性、手术室利用率与总患者优先级之间的权衡关系。研究结果为医院在资源有限时如何平衡患者可及性、运营效率及医护人员工作量提供了管理层面的见解。
英文摘要
This paper addresses the integrated Master Surgical Scheduling Problem and Surgical Case Assignment Problem under weekend bed capacity constraints. We propose a joint optimization framework that simultaneously determines the assignment of specialties and surgeons to Operating Room (OR) blocks, the selection and assignment of patients to these blocks, and the sequencing of surgeries, while accounting for reduced bed availability during weekends. The model is formulated as a multi-criteria Mixed-Integer Linear Program (MILP) that prioritizes the total priority-weighted amount of scheduled patients, minimizes excess weekend bed occupancy, and maximizes OR utilization. To solve large instances, we develop a Column Generation (CG) algorithm in which the pricing subproblem is formulated as a Resource-Constrained Shortest Path Problem. The framework accommodates block, open, and modified block scheduling policies. Computational experiments show that the CG approach outperforms the direct MILP solution in terms of solution quality and computational time, particularly for larger instances. We further analyze the trade-offs between weekend bed availability, OR utilization, and total patient priority. Our results provide managerial insights into how hospitals can balance patient access, operational efficiency, and staff workload when resources are limited.
