A fast-response mathematical programming approach for delivering disaster relief goods: an earthquake case study

作     者：Qezelbash-Chamak, Jaber Badamchizadeh, Saeid Seifi, Abbas 

作者机构：Univ Florida Dept Ind & Syst Engn Gainesville FL 32611 USA Amirkabir Univ Technol Dept Ind Engn & Management Syst Tehran Iran 

出 版 物：《TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH》 (Transp. Lett.)

年 卷 期：2024年第16卷第9期

页      面：1091-1114页

核心收录：

学科分类：08[工学] 0823[工学-交通运输工程] 

基　　金：The authors are very grateful to the anonymous reviewers  the journal editor-in-chief  and associate editors  whose constructive comments and insightful critiques resulted in a much-improved paper. We also thank those who provided comments on earlier versi 

主　　题：Disaster management humanitarian logistics location two-stage stochastic programming branch and cut Benders decomposition 

摘      要：This paper tackles a complex logistics challenge of disaster management, encompassing warehouse location, pre-disaster inventory planning, routing, and post-disaster relief supply delivery. We establish an iterative process for optimizing relief distribution to shelters. Adaptable warehouse inventory reallocation responds to fluctuating demands, guided by a two-phase mathematical programming approach. In the first phase, a two-stage stochastic programming (TSSP) model determines optimal warehouse and shelter locations and inventory levels. In the subsequent phase, we introduce a mixed-integer programming (MIP) model to minimize the overall delivery time by making routing decisions. To streamline the process, we introduce a novel enumeration algorithm that trims down route options by considering unavailable links, effectively transforming the MIP model into an assignment-based model. This innovation results in a noticeable 74% reduction in solution time. Further efficiency is achieved by developing a branch-and-cut algorithm for swift MIP resolution. A real-world case study confirms the practicality of our approach.