Research on the Location Selection of Agricultural Product Distribution Centers Based on Genetic Algorithm
- DOI
- 10.2991/978-94-6463-736-6_25How to use a DOI?
- Keywords
- Fresh agricultural products; Site Selection Optimization; Genetic Algorithm
- Abstract
This paper focuses on the problems of concentrated location selection and high costs of agricultural product distribution centers. Taking Xinjiang as the research object, a location - selection model for agricultural product distribution centers based on the genetic algorithm is constructed. This model comprehensively considers multiple costs such as construction, management, and processing, and simplifies the problem through assumptions. Meanwhile, improved strategies like hybrid coding are adopted to optimize the genetic algorithm for solving the model. A simulation analysis is carried out using MATLAB with a case of a logistics enterprise in Xinjiang. The results show that choosing Ürümqi and Aksu as the locations of distribution centers is the optimal choice, which can reduce the total cost and verify the effectiveness of the model and the algorithm, providing a reference for the location - selection of agricultural product distribution centers.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Hang Shang AU - Yuxin Zhang PY - 2025 DA - 2025/05/22 TI - Research on the Location Selection of Agricultural Product Distribution Centers Based on Genetic Algorithm BT - Proceedings of the 2025 4th International Conference on Engineering Management and Information Science (EMIS 2025) PB - Atlantis Press SP - 218 EP - 223 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-736-6_25 DO - 10.2991/978-94-6463-736-6_25 ID - Shang2025 ER -