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Genetic Algorithm Based on the Number of Distribution Centers for Uncertain Emergency Supplies Vehicle scheduling study

Published: 29 May 2024 Publication History

Abstract

Major emergencies in recent years have greatly challenged the rapid response capability of the emergency supplies logistics system. In order to minimize the damage brought by emergencies to the society, the emergency supplies should be timely to the place where the emergencies occur, so as to reduce the losses brought by the emergencies. In order to further study the vehicle scheduling of emergency supplies, this paper establishes a multi-distribution centre emergency logistics vehicle scheduling model in the context of emergency logistics, considering the number of distribution centres in different cases, with the goal of reaching the demand point in terms of the total time and the total cost, and giving the time goal a higher weight, and solving it by using the genetic algorithm. The simulation solution is carried out through the arithmetic example, and the following conclusions are drawn: (1) in the ideal situation, the more the number of distribution centres is, the total time for emergency supplies to reach the demand point is the smallest, but the total cost tends to be higher; (2) the model in this paper can find the optimal solution that meets the conditions for the different number of distribution centres, which improves the distribution tenacity of the distribution centres. Therefore, the research in this paper provides scientific and effective suggestions for emergency logistics decision makers.

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  1. Genetic Algorithm Based on the Number of Distribution Centers for Uncertain Emergency Supplies Vehicle scheduling study

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      cover image ACM Other conferences
      BDEIM '23: Proceedings of the 2023 4th International Conference on Big Data Economy and Information Management
      December 2023
      917 pages
      ISBN:9798400716669
      DOI:10.1145/3659211
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Published: 29 May 2024

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