A hybrid memetic metaheuristic for medical staff assignment in major public health emergencies

IF 4.3 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Operations Research Pub Date : 2025-08-30 DOI:10.1016/j.cor.2025.107256

Yang Wang , He Zheng , Zequn Wei , Christophe Wilbaut , Saïd Hanafi

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引用次数: 0

Abstract

During major public health emergencies, effective assignment of medical staff is crucial for saving lives and controlling the spread of epidemics. This work focuses on the assignment of doctors and nurses to hospitals to form treatment groups that carry out patient treatment tasks. We consider the practical constraints of skill types of medical staff and the severity of patients’ conditions and propose a mixed integer programming model with the objective of maximizing demand satisfaction and personnel skill matching. To solve this problem, we introduce a hybrid memetic search algorithm that combines a specialized crossover operator for generating promising offspring solutions and a variable neighborhood search procedure to improve their quality. Computational results demonstrate that our algorithm outperforms the general mixed integer programming solver GUROBI. The key components of the proposed algorithm are experimentally analyzed and managerial insights are derived.

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重大突发公共卫生事件中医务人员分配的混合模因元启发式

在重大突发公共卫生事件中，有效分配医务人员对于挽救生命和控制流行病传播至关重要。这项工作的重点是将医生和护士分配到医院，组成治疗小组，执行患者治疗任务。考虑到医务人员技能类型的实际限制和患者病情的严重程度，提出了以需求满意度和人员技能匹配最大化为目标的混合整数规划模型。为了解决这一问题，我们引入了一种混合模因搜索算法，该算法结合了一个专门的交叉算子来产生有希望的后代解和一个可变邻域搜索过程来提高后代解的质量。计算结果表明，该算法优于一般的混合整数规划求解器GUROBI。实验分析了该算法的关键组成部分，并得出了管理见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computers & Operations Research 工程技术-工程：工业

CiteScore

8.60

自引率

8.70%

发文量

292

审稿时长

8.5 months

期刊介绍： Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.