Abstract: Emergency surgical scheduling is an important measure to improve operative efficiency and save lives after emergent public events. For instance, since the late of 2019, COVID-19 has swept the world. As an epidemic disaster, COVID-19 has produced a serious impact on over 100 countries and nearly 657 million people have been infected worldwide. In 2021, Haiti suffered a 7.3-magnitude earthquake. At least 2248 people were dead, 329 missing and 12268 injured. To deal with emergent public events, most scholars have focused on emergency monitoring and post-traumatic stress disorder, PTSD. Few scholars pay attention to improving the emergency rescue ability of hospitals for injured people. Patients should receive surgeries as soon as possible after an emergent public event, but the allocation is a complex issue. Centralized coordination is a prerequisite to promote the rescue efficiency, so as to match the limited medical resources with the demands of emergency surgery. Additionally, the resource involved in operating rooms (ORs) accounts for more than 40% of the total resources of the hospital, and surgeries contribute to a substantial portion of hospital revenue and healthcare systems. Therefore, the feasible surgical scheduling for OR-related resource is conducive to enhancing the ability of hospitals' rapid response to emergent public events.
Surgical scheduling with deterioration is a derivative study of the job-shop scheduling problem based on deterioration effect. Some scholars consider the deterioration effect in a flexible job-shop scheduling model. They express the deterioration effect as a linear increasing relationship between the actual processing time and starting processing time of the job. So far, the deterioration effect has been studied in scheduling problems, but the existing literature has mostly focused on the single deterioration effect in job-shop scheduling. It is rare to consider deterioration effects of both patients and surgeons at the same time when studying the dynamic emergency surgical scheduling problem. Generally, the emergency surgical procedure can be divided into preoperative, intraoperative and postoperative stages. In this paper, the dual deteriorating effects of prolonged patient non-treatment and prolonged surgeon work hours, as well as the characteristics of emergency insertion of critical patients, are considered in emergency surgical scheduling. Based on this, a multi-objective dynamic emergency surgical scheduling (MODESSP) model is established with the aim of minimizing the maximum completion time of surgical operations and mean operation time. An improved multi-objective slime mould algorithm (IMOSMA) is designed to solve the MODESSP problem. Furthermore, the random parameter adaptive adjustment and Tent chaotic mapping are introduced to enhance the global optimization search ability of the solution space.
This study has certain application value for hospital emergency surgical scheduling, which is embodied in two aspects. (1)The traditional surgical scheduling problem does not consider the influence of two-sided relationship between surgeons and patients. In this study, a MODESSP model is established for the first time by comprehensively considering the dual deterioration effects and emergency insertion of critical patients. (2)The proposed MODESSP model pays more attention to the surgeon and patient experiences and the impact of dynamic events on surgical scheduling, which can deeply portray the actual dynamic emergency surgical scheduling in hospitals. (3)The optimal surgical scheduling scheme can help hospital managers to balance the goals of surgery time, workloads of medical staff and OR simultaneously in the healthcare system, thereby improving surgical efficiency and medical resource utilization. In practical application, based on the improvement idea of IMOSMA, a more efficient surgical scheduling system can be designed to increase the efficiency of surgical scheduling in hospitals and to promote the construction of “people-oriented” humanized modern hospital.

Key words: dual deterioration effects, emergency surgery, dynamic scheduling, IMOSMA

摘要： 应急手术调度是突发公共事件后提高手术效率,挽救生命的重要措施。将应急手术过程分为手术前、中、后三个阶段,考虑患者长时间未能接受治疗和医生长时间工作而产生的双重恶化效应,同时针对实际手术调度危重患者紧急插入的特点,构建以手术最大完成时间和患者平均手术时间为优化目标的多目标动态应急手术调度模型。设计改进黏菌算法(IMOSMA)并对动态应急手术调度问题进行求解,将随机参数自适应调整和Tent混沌扰动引入黏菌算法,提高算法全局寻优能力。最后,仿真模拟实验表明改进黏菌算法能有效解决动态应急手术调度问题。

关键词: 双重恶化效应, 应急手术, 动态调度, 改进黏菌算法