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Research on location selection model of distribution network with constrained line constraints based on genetic algorithm

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Abstract

With the rapid rise of the Internet, China’s e-commerce has also flourished. The development of e-commerce has led to an increase in the volume of logistics and distribution. The further development of e-commerce has also placed higher demands on the timeliness of logistics and distribution. The competition of e-commerce companies has shifted from the competition between business models to the competition between logistics services. The scientific and rational distribution site selection planning is the prerequisite and guarantee for the efficient operation of logistics distribution network. To balance the contradiction between logistics distribution speed and distribution cost has become the key to competition among e-commerce companies. This paper analyzes the current network structure and distribution mode of e-commerce logistics city distribution, and analyzes and discusses the problems existing in current e-commerce logistics city distribution. Furthermore, the bi-level programming is studied. According to the characteristics of the bi-level programming problem, the genetic algorithm flow suitable for bi-level programming is proposed. The bi-level programming model of urban distribution service network site selection with limited lines is proposed. Through the verification of the genetic algorithm in this paper, the proposed method can plan a reasonable service site location layout and distribution models and path selection. The results show that the average daily fuel cost can be reduced by 37.6%, and the transportation distance and fuel cost can be optimized best.

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Acknowledgements

This work was supported by Soft Scientific Research Projects in Henan Province, China (ID: 172400410013), Special Project on Innovation Method Work of China Ministry of Science and Technology (ID: 2017IM060100), Henan Province Philosophy and Social Affairs Office Planning Project (2016G013), CERNET Innovation Project (ID: NGII20160902), Key Scientific Research Projects in Henan Province, China (ID: 17A630016). The authors declare that there is no conflict of interest with any financial organizations regarding the material reported in this manuscript.

The authors do not have any possible conflicts of interest.

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Authors and Affiliations

  1. School of Management, Henan University of Science and Technology, Luoyang, China

    Kai Guo

  2. Henan Province Collaborative Innovation Center of Nonferrous Metals, Luoyang, China

    Kai Guo

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  1. Kai Guo
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Correspondence to Kai Guo.

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Guo, K. Research on location selection model of distribution network with constrained line constraints based on genetic algorithm. Neural Comput & Applic 32, 1679–1689 (2020). https://doi.org/10.1007/s00521-019-04257-y

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