Research on the Distribution of Emergency Supplies during the COVID-19 Epidemic

Jian-guo Zheng, Qing Yang, Shui-lin Chen and Wen-Long Shang

Complexity, 2023, vol. 2023, 1-17

Abstract: The COVID-19 virus spreads quickly and is highly contagious, and the timeliness of emergency supplies is extremely demanding, so adequate and efficient emergency supplies have become a necessary prerequisite for strict prevention and control during the outbreak. However, the available research results are still relatively few, and using the brain storm optimization algorithm to solve the emergency supplies distribution problem is still blank. In order to optimize the emergency supplies distribution system in the context of COVID-19, this paper studies the open vehicle routing problem by considering the load weight constraints, demand constraints, and time window constraints. With the shortest total distribution distance as the objective function, a mathematical model of mixed integer linear programming is established, and the crossover operation of the genetic algorithm, the destruction operator and the repair operator of the large neighborhood search algorithm are introduced in the brain storm optimization algorithm to enhance the diversity of the solution while making the solution toward the optimal direction. Through the verification of two sets of examples, we found that compared with the other 13 solution algorithms, the solution capability and solution efficiency of the brain storm optimization algorithm are better than the comparison algorithms, which can significantly reduce the length of the distribution route and lower the distribution cost, and has excellent convergence and stability. Meanwhile, it can effectively improve the distribution efficiency of emergency supplies, which is of great significance to help the emergency reception and regular prevention and control during the outbreak of the COVID-19 epidemic. In addition, it has the necessary guidance for the improvement of personnel efficiency in the supply chain and logistics industry.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:9023040

DOI: 10.1155/2023/9023040

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