Application on Cold Chain Logistics Routing Optimization Based on Improved Genetic Algorithm
- Authors: Liyi Zhang 1, Gao Y.2, Sun Y.1, Fei T.1, Wang Y.2
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Affiliations:
- Information Engineering College, Subidhanagar
- Economic College, Tianjin University of Commerce
- Issue: Vol 53, No 2 (2019)
- Pages: 169-180
- Section: Article
- URL: https://journals.rcsi.science/0146-4116/article/view/175815
- DOI: https://doi.org/10.3103/S0146411619020032
- ID: 175815
Cite item
Abstract
As the rise of fresh e-supplier, cold chain logistic has become the hot topics in China. But due to its special timeliness, it is necessary to optimize its vehicle routing. Firstly, we construct a cold chain logistics vehicle routing optimization with soft time windows model. Secondly, as simple genetic algorithm has some shortcomings such as poor population diversity and slow convergence, we propose an improved genetic algorithm – seeker genetic algorithm. By combining the uncertainty reasoning behavior in the seeker optimization algorithm and the nearest neighbor strategy, we improve the mutation operator in the genetic algorithm. Finally, we solve the cold chain logistics vehicle routing optimization model with basic genetic algorithm and seeker genetic algorithm respectively. The results indicate that seeker genetic algorithm could find the path with lower cost.
About the authors
Liyi Zhang
Information Engineering College, Subidhanagar
Email: sunyunshan@tjcu.edu.cn
Nepal, TinkuneKathamandu, Post Box: 12277
Yang Gao
Economic College, Tianjin University of Commerce
Email: sunyunshan@tjcu.edu.cn
China, Tianjin P.R. , 300134
Yunshan Sun
Information Engineering College, Subidhanagar
Author for correspondence.
Email: sunyunshan@tjcu.edu.cn
Nepal, TinkuneKathamandu, Post Box: 12277
Teng Fei
Information Engineering College, Subidhanagar
Email: sunyunshan@tjcu.edu.cn
Nepal, TinkuneKathamandu, Post Box: 12277
Yujing Wang
Economic College, Tianjin University of Commerce
Email: sunyunshan@tjcu.edu.cn
China, Tianjin P.R. , 300134