School of Economics and Management, Beijing Information Science and Technology University, Beijing, China.
Fire Fighting Theory Laboratory, Shanghai Fire Science and Technology Research Institute of MEM, Shanghai, China.
PLoS One. 2024 Jul 26;19(7):e0305349. doi: 10.1371/journal.pone.0305349. eCollection 2024.
The increasingly frequent occurrence of major natural disasters can pose a serious threat to national stability and the safety of people's lives, and cause serious economic losses. How to quickly and accurately dispatch emergency materials to all disaster areas across regions in post-disaster has attracted wide attention from the government and academia. In response to the characteristic of high uncertainty in emergency rescue for major natural disasters, and considering differentiated disaster severity levels in different disaster areas, the entropy weight method is used to determine the urgency coefficient of emergency material demand for disaster areas. This study aims to minimize the emergency materials dispatching time and cost, also maximize the dispatching fairness for disaster areas. The triangular fuzzy number method is used to represent the uncertain variables mentioned above, so that a cross-regional emergency materials intelligent dispatching model in major natural disasters (CREMIDM-MND) is constructed. The extremely heavy rainstorm disaster in Henan Province of China in 2021 is selected as a typical case. Based on objective disaster data obtained from official websites, this study applies the constructed model to real disaster case and calculates the results by MATLAB. The ant colony algorithm is further used to optimize the transportation route based on the calculation results of the emergency material dispatching for disaster areas, and finally forms the intelligent emergency materials dispatching scheme that meets the multiple objectives. The research results indicate that compared to the actual situation, CREMIDM-MND can help decision-maker to develop a cross-regional emergency materials intelligent dispatching scheme in time, thereby effectively improving the government's emergency rescue performance in major natural disasters. Moreover, some managerial insights related to cross-regional emergency materials dispatching practice problem in major natural disasters are presented.
日益频繁的重大自然灾害的发生，对国家稳定和人民生命安全构成严重威胁，并造成严重的经济损失。如何在灾后迅速、准确地将应急物资调配到各地区的灾区，引起了政府和学术界的广泛关注。针对重大自然灾害应急救援中高度不确定性的特点，考虑到不同灾区灾害严重程度的差异，利用熵权法确定灾区应急物资需求的紧急系数。本研究旨在最小化应急物资的调度时间和成本，同时最大化灾区的调度公平性。采用三角模糊数方法来表示上述不确定变量，构建了重大自然灾害跨区域应急物资智能调度模型（CREMIDM-MND）。选取 2021 年中国河南省特大暴雨灾害作为典型案例。基于官方网站获取的客观灾害数据，将构建的模型应用于实际灾害案例，并通过 MATLAB 进行计算。进一步利用蚁群算法基于灾区应急物资调度的计算结果优化运输路线，最终形成满足多目标的智能应急物资调度方案。研究结果表明，与实际情况相比，CREMIDM-MND 可以帮助决策者及时制定跨区域应急物资智能调度方案，从而有效提高政府在重大自然灾害中的应急救援能力。此外，还提出了一些与重大自然灾害跨区域应急物资调度实践问题相关的管理见解。
