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Application on Cold Chain Logistics Routing Optimization Based on Improved Genetic Algorithm

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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.

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Authors and Affiliations

  1. Information Engineering College, Subidhanagar, Post Box: 12277, Tinkune, Kathamandu, Nepal

    Liyi Zhang, Yunshan Sun & Teng Fei

  2. Economic College, Tianjin University of Commerce, 300134, Tianjin, P.R. , China

    Yang Gao & Yujing Wang

Authors
  1. Liyi Zhang
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  2. Yang Gao
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  3. Yunshan Sun
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  4. Teng Fei
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  5. Yujing Wang
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Correspondence to Yunshan Sun.

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Liyi Zhang, Gao, Y., Sun, Y. et al. Application on Cold Chain Logistics Routing Optimization Based on Improved Genetic Algorithm. Aut. Control Comp. Sci. 53, 169–180 (2019). https://doi.org/10.3103/S0146411619020032

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  • DOI: https://doi.org/10.3103/S0146411619020032

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