Optimization and Integration of Logistics Facilities Resources Based on Genetic-Simulated Annealing Hybrid Algorithm

Abstract

A huge pressure has been brought to the express delivery industry with the rapid development of e-commerce. In order to improve efficiency and save resources, the joint distribution mode is applied in more and more cities. Under the joint distribution mode, it is an urgent problem to be solved that how to optimize and integrate the urban terminal distribution network. This paper proposes a two-level urban terminal distribution network optimization integration model with low cost as the objective. The two-level network is made up of distribution center, terminal node, and customer cluster. And the relationship of business between the three of them is many to many. In order to solve this model, an approximation algorithm is designed and implemented, which is the genetic-simulated annealing hybrid algorithm (GASA) based on neighborhood search included four rules. This paper also implements two decomposition algorithms based on immune genetic algorithm (GA) and simulated annealing algorithm (SA) to solve the model. By comparing the results of the three algorithms, the integrated effect of the two-level urban terminal distribution network, utilizing the GASA proposed in this paper, is significantly better than two decomposition algorithms. The result of the GASA is 20% better than the other two decomposition algorithms on average.