Fresh Produce Delivery Path Optimization Based on Improved Genetic Algorithm

DOI

10.2991/978-94-6463-570-6_96How to use a DOI?

Keywords

Cold chain logistics; Time window; Improved genetic algorithm; Path optimization

Abstract

Aiming at the current problems of low transportation on-time rate and high product spoilage rate in the cold chain logistics industry, we constructed a fresh produce distribution path optimization model considering the fixed cost, transportation cost, cargo damage cost, refrigeration cost and time window penalty cost minimization, and solved the model by using improved genetic algorithm. The results show that the total cost after optimization is reduced by 8% compared with the pre-optimization, and the total distance is reduced by 13% compared with the pre-optimization. It is verified that the improved genetic algorithm is more effective than the traditional genetic algorithm through examples.

Copyright

© 2024 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.

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TY  - CONF
AU  - Zheng Yang
AU  - Xinlei Li
PY  - 2024
DA  - 2024/11/22
TI  - Fresh Produce Delivery Path Optimization Based on Improved Genetic Algorithm
BT  - Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024)
PB  - Atlantis Press
SP  - 963
EP  - 971
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-570-6_96
DO  - 10.2991/978-94-6463-570-6_96
ID  - Yang2024
ER  -