Intelligent dispatching optimization of emergency supplies to multidisaster areas in major natural disasters
ZHANG Lin1, WANG Jinyu1, WANG Xin1, WANG Wei2, QU Li1
1. School of Economics and Management, Beijing Information Science and Technology University, Beijing 100192, China; 2. Fire Fighting Theory Laboratory, Shanghai Fire Science and Technology Research Institute of Ministry of Emergency Management, Shanghai 200032, China
Abstract:The frequent occurrence of major natural disasters not only endangers national stability and people's safety but also causes serious economic losses. Since most sudden natural disasters are unpredictable, how to transport emergency supplies to disaster-affected areas quickly and accurately has attracted wide attention. Unlike existing research, this study begins with the rescue characteristics of major natural disasters. In this study, an intelligent dispatching model of emergency supplies for multidisaster areas is constructed considering. Considering that the emergency materials of each rescue area to meet the needs of each disaster area, this study constructs an uncertain multiobjective intelligent dispatching model of emergency supplies in fully. Due to the uncertainty and fuzziness of information in emergency situations, using triangular fuzzy number method can help decision-makers to make effective decisions. Therefore, triangular fuzzy number method is used to express the uncertainty of emergency supplies demand and transportation time in different disaster areas. The rainstorm disaster in Henan Province, China, in 2021 is taken as a typical case in this study. The objective and actual data of emergency supplies dispatched in this disaster are obtained from the official websites of Zhengzhou Temporary Disaster Relief Reserve, Red Cross Society of China Henan Branch, and Henan Charity Network. This study sets emergency supplies as variable x(Ze)ij, unit cost as variable cij, transportation time as a variable tij. According to the triangular fuzzy number of emergency supplies demand and transportation time which set in this study, the uncertain variables are represented by the triangular fuzzy number method. Thus, the model is transformed into a deterministic multiobjective intelligent dispatching model. Two-dimensional Euclidean distance weighting is used to simulate the calculation and solve the model. Then, the linear interactive and general optimizer (LINGO) software is used to calculate the emergency supplies dispatching strategy from each rescue area to each disaster area. Given the actual situation of limited transportation conditions, each rescue area is usually unable to dispatch all emergency supplies at one time. Therefore, the weight of various emergency supplies is determined according to the urgency of the actual situation, and the LINGO software is used again in this study to calculate the phased emergency supplies transportation scheme. Finally, the optimal emergency dispatching strategy is formulated to meet the research objective in this study. Based on the above, a visual comparison is made between the results obtained using the constructed emergency supplies intelligent dispatching model and the demand quantity of emergency supplies in each disaster area. It can be seen that the dispatching quantity of various emergency supplies obtained by the model in this work has little difference from the actual emergency supply demand of each disaster area. As a result, large waste in major natural disasters can be avoided. The research findings show that the model has high reliability, and the simulation results are close to the actual situation. It can meet the emergency supplies demand of multidisaster areas and help decision-makers develop effective disaster relief strategies in major natural disasters.
张琳, 王金玉, 王鑫, 王伟, 曲立. 重大自然灾害下多灾害点应急物资智能调度优化[J]. 清华大学学报(自然科学版), 2023, 63(5): 765-774.
ZHANG Lin, WANG Jinyu, WANG Xin, WANG Wei, QU Li. Intelligent dispatching optimization of emergency supplies to multidisaster areas in major natural disasters. Journal of Tsinghua University(Science and Technology), 2023, 63(5): 765-774.
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