College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Building N3963, 16273, Saudi Arabia.
LARODEC, Institut Supérieur de Gestion de Tunis, Université de Tunis, 41 Ave de la Liberte, Tunis, 2000, Tunisia.
Med Biol Eng Comput. 2022 May;60(5):1295-1311. doi: 10.1007/s11517-022-02513-3. Epub 2022 Mar 22.
This study presents an efficient solution for the integrated recovery room planning and scheduling problem (IRRPSP). The complexity of the IRRPSP is caused by several sources. The problem combines the assignment of patients to recovery rooms and the scheduling of caregivers over a short-term planning horizon. Moreover, a solution of the IRRPSP should respect a set of hard and soft constraints while solving the main problem such as the maximum capacity of recovery rooms, the maximum daily load of caregivers, the treatment deadlines, etc. Thus, the need for an automated tool to support the decision-makers in handling the planning and scheduling tasks arises. In this paper, we present an exhaustive description of the epidemiological situation within the Kingdom of Saudi Arabia, especially in Jeddah Governorate. We will highlight the importance of implementing a formal and systematic approach in dealing with the scheduling of recovery rooms during extreme emergency periods like the COVID-19 era. To do so, we developed a mathematical programming model to present the IRRPSP in a formal way which will help in analyzing the problem and lately use its solution for comparison and evaluation of our proposed approach. Due to the NP-hard nature of the IRRPSP, we propose a hybrid three-level approach. This study uses real data instances received from the Department of Respiratory and Chest Diseases of the King Abdulaziz Hospital. The computational results show that our solution significantly outperforms the results obtained by CPLEX software with more than 1.33% of satisfied patients on B1 benchmark in much lesser computation time (36.27 to 1546.79 s). Moreover, our proposed approach can properly balance the available nurses and the patient perspectives.
本研究提出了一种综合恢复室规划和调度问题（IRRPSP）的有效解决方案。IRRPSP 的复杂性源于多个来源。该问题将患者分配到恢复室和在短期规划期内安排护理人员结合在一起。此外，解决 IRRPSP 的解决方案应在解决主要问题（如恢复室的最大容量、护理人员的最大日工作量、治疗截止日期等）的同时尊重一系列硬约束和软约束。因此，需要自动化工具来支持决策者处理规划和调度任务。在本文中，我们对沙特阿拉伯王国，特别是吉达省的流行病学情况进行了全面描述。我们将强调在 COVID-19 时代等极端紧急时期实施正式和系统的方法来处理恢复室调度的重要性。为此，我们开发了一个数学规划模型，以正式的方式呈现 IRRPSP，这将有助于分析问题，并最终使用其解决方案来比较和评估我们提出的方法。由于 IRRPSP 的 NP 难性质，我们提出了一种混合三层方法。本研究使用从阿卜杜勒阿齐兹国王医院呼吸和胸部疾病科收到的真实数据实例。计算结果表明，我们的解决方案在 B1 基准上的满意度患者比 CPLEX 软件的结果高出 1.33%以上，而计算时间（36.27 到 1546.79 秒）却少得多。此外，我们提出的方法可以适当平衡可用护士和患者的观点。
