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Improved Genetic Algorithm Based Cold Chain Logistics Path Planning with Time Window

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DOI: 10.23977/ieim.2023.060407 | Downloads: 18 | Views: 532


Yuanyuan Li 1, Xiaoyu Xu 1, Xuelian Guo 1, Xuefeng Liu 1


1 Business School, Shandong University of Technology, Zibo, Shandong, 255000, China

Corresponding Author

Yuanyuan Li


To solve the problems of high distribution costs and unreasonable distribution paths of M cold chain company, a cold chain logistics path planning problem with a single distribution centre under a soft time window is proposed. The objective of optimization is to minimize the total costs incurred in the cold chain logistics distribution process and to improve efficiency through rational path planning. Based on the general vehicle path system, the conventional process of the traditional genetic algorithm is introduced, and improvements are made in the genetic selection, crossover and mutation links to design an improved genetic algorithm that introduces a migration strategy and improves the shortcomings of the traditional heritage algorithm that tends to converge prematurely. An empirical study is conducted to solve the optimal route for the problems existing in the current cold chain distribution status quo of Company M. The effectiveness and feasibility of the model and algorithm are confirmed to provide reference for the cold chain logistics and distribution industry.


Path planning, time windows, vehicle distribution, genetic algorithm


Yuanyuan Li, Xiaoyu Xu, Xuelian Guo, Xuefeng Liu, Improved Genetic Algorithm Based Cold Chain Logistics Path Planning with Time Window. Industrial Engineering and Innovation Management (2023) Vol. 6: 44-52. DOI:


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