A two-stage robust optimization model for emergency service facilities location-allocation problem under demand uncertainty and sustainable development

作     者：Li, Hongyan Yu, Dongmei Zhang, Yiming Yuan, Yifei 

作者机构：Liaoning Tech Univ Ordos Inst Ordos 017004 Peoples R China Liaoning Tech Univ Sch Business Adm Huludao 125105 Peoples R China Liaoning Tech Univ Inst Optimizat & Decis Analyt Fuxin 123000 Peoples R China 

出 版 物：《SCIENTIFIC REPORTS》 (Sci. Rep.)

年 卷 期：2025年第15卷第1期

页      面：1-18页

核心收录：

基　　金：National Natural Science Foundation of China University-Local Government Scientific and Technical Cooperation Cultivation Project of Ordos Institute-LNTU [YJY-XD-2024-B-016] Ministry of Education in China of Humanities and Social Science Project [21YJCZH204] Liaoning Provincial Department of Education [JYTZD2023072, LJ112410147046] Natural Science Foundation of Liaoning Province [2024-MS-206] 12201275 

主　　题：Emergency service facilities Location-allocation Two-stage robust optimization Demand uncertainty Sustainable development 

摘      要：Under the backdrop of frequent emergencies, the rational layout of emergency service facilities (ESF) and the effective allocation of emergency supplies have emerged as crucial in determining the timeliness of post-disaster response. By adequately accounting for potential uncertainties and carrying out comprehensive pre-planning, the robustness of location-allocation decisions can be significantly improved. This paper delves into the ESF network design problem under demand uncertainty and formulates this problem as a two-stage robust optimization model. The presented model defines a generalized budget uncertainty set to capture victims uncertain demand and minimizes the sum of the costs involved in the two stages. The objective function integrates the input cost in the preparedness phase, the deprivation cost from the victims perspective and the environmental impact cost responding to sustainable development in the response phase, which respectively correspond to the comprehensive optimization of the deployment of ESF, the distribution of emergency supplies and the implementation of sustainable measures. Subsequently, we employ the column and constraint generation (C&CG) algorithm to solve the proposed model and take the COVID-19 epidemic in Wuhan as a case to verify the effectiveness of the model and algorithm. Finally, we examine the influence of demand uncertainty and environmental impact cost on the optimal solution, yielding valuable managerial insights.