• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science ›› 2024, Vol. 46 ›› Issue (01): 159-169.

• Artificial Intelligence and Data Mining • Previous Articles     Next Articles

Research on path optimization of express terminal location based on hybrid heuristic algorithm

SUN Rui-nan1,CHU Xiang1,CHEN Yu2,YAN Ming-ning1   

  1. (1.School of Shipping Economics and Management,Dalian Maritime University,Dalian 116026;
    2.Comprehensive Transportation Collaborative Innovation Center,Dalian Maritime University,Dalian 116026,China)
  • Received:2022-04-04 Revised:2022-10-12 Accepted:2024-01-25 Online:2024-01-25 Published:2024-01-15

Abstract: The traditional express terminal distribution mode has problems such as redundant construction of express outlets and overlapping delivery paths, and the joint distribution model can effectively solve these problems. Therefore, this paper studies the location path of express terminal outlets in the case of simultaneous receiving and dispatching and uncertain receiving demand under the joint distribution model. Firstly, a two-stage mathematical optimization model is established to deal with the problem of uncertain receipt volume by introducing random chance constraints. Secondly, a hybrid heuristic algorithm based on genetic algorithm and adaptive large neighborhood search algorithm is designed. Finally, numerical experiments show that the designed hybrid algorithm has a faster convergence speed and better solution quality than the traditional genetic algorithm. Too high or low risk acceptance of the optimization scheme in the random demand environment will lead to the increase of cost. With the increase of the ratio of customer receiving and dispatching volume, the cost of express terminal distribution first decreases and then increases, The nearest outlet return strategy can effectively reduce the distribution cost of enterprises. 

Key words: joint distribution, location routing problem, genetic algorithm, adaptive large neighborhood search algorithm, express outlets