Research on Route Optimization for Dairy Cold Chain Logistics Based on Hybrid Genetic Algorithm
- DOI
- 10.2991/978-94-6239-758-3_59How to use a DOI?
- Keywords
- Cold chain logistics; Route optimization; Genetic algorithm; A* algorithm
- Abstract
Due to the perishable nature of dairy products, dairy cold chain logistics has high requirements for temperature control and distribution timeliness. This paper aims to optimize urban dairy cold chain logistics to minimize the total distribution cost by reducing delivery time, lowering cargo loss, and ensuring the quality of dairy products. First, a multi-objective mathematical model is constructed that integrates fixed cost, transportation cost, cargo damage cost, refrigeration cost, penalty cost, and carbon emission cost, while fully considering the perish ability of dairy products during transportation and loading/unloading. Second, a hybrid genetic algorithm combining the A* algorithm and genetic algorithm is designed to solve the model. Finally, the results show that the hybrid genetic algorithm outperforms the single genetic algorithm in cost reduction, which verifies the effectiveness of the proposed algorithm.
- Copyright
- © 2026 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 - Guangyuan Xi PY - 2026 DA - 2026/09/08 TI - Research on Route Optimization for Dairy Cold Chain Logistics Based on Hybrid Genetic Algorithm BT - Proceedings of the 2026 7th International Conference on Management Science and Engineering Management (ICMSEM 2026) PB - Atlantis Press SP - 597 EP - 606 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6239-758-3_59 DO - 10.2991/978-94-6239-758-3_59 ID - Xi2026 ER -