Optimising the Distribution of Multi-Cycle Emergency Supplies after a Disaster

Fuyu Wang, Xuefei Ge (), Yan Li, Jingjing Zheng and Weichen Zheng
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Fuyu Wang: School of Management Science and Engineering, Anhui University of Technology, Maanshan 243032, China
Xuefei Ge: School of Management Science and Engineering, Anhui University of Technology, Maanshan 243032, China
Yan Li: School of Management Science and Engineering, Anhui University of Technology, Maanshan 243032, China
Jingjing Zheng: School of Mathematical Sciences, Huaibei Normal University, Huaibei 235000, China
Weichen Zheng: School of Management Science and Engineering, Anhui University of Technology, Maanshan 243032, China

Sustainability, 2023, vol. 15, issue 2, 1-26

Abstract: In order to achieve rapid and fair distribution of emergency supplies after a large-scale sudden disaster, this paper constructs a comprehensive time perception satisfaction function and a comprehensive material loss pain function to portray the perceived satisfaction of disaster victims based on objective constraints such as limited transport, multimodal transport and supply being less than demand, and at the same time considers the subjective perception of time and material quantity of disaster victims under limited rational conditions, and constructs a multi-objective optimisation model for the dispatch of multi-cycle emergency supplies by combining comprehensive rescue cost information. For the characteristics of the proposed model, based on the NSGA-II algorithm, generalized reverse learning strategy, coding repair strategy, improved adaptive crossover, variation strategy, and elite retention strategy are introduced. Based on this, we use the real data of the 2008 Wenchuan earthquake combined with simulated data to design corresponding cases for validation and comparison with the basic NSGA-II algorithm, SPEA-II and MOPSO algorithms. The results show that the proposed model and algorithm can effectively solve the large-scale post-disaster emergency resource allocation problem, and the improved NSGA- II algorithm has better performance.

Keywords: large-scale sudden-onset disasters; perceived satisfaction; emergency material distribution; multi-objective optimisation; improved NSGA-II algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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