Meta-heuristic Logistics Network Optimization Algorithm Based on Graph Neural Network
ZHOU Qianxi
SUN Geng
Abstract：The research on logistics network optimization methods is of great significance to improve logistics efficiency.How-ever,the existing logistics network optimization algorithms have problems such as high computational complexity and easy to fall in-to local optimum,so this paper proposes a meta-heuristic logistics network optimization algorithm based on graph neural network.The graph neural network policy model is used to realize the intelligence of the meta-heuristic method.The model captures node fea-tures and calculates weights through the graph convolution mechanism to obtain the global optimal solution.Experimental results on CVRP dataset show that the proposed algorithm can effectively solve the problem of logistics network optimization.
Keywords：graph neural networksmeta-heuristiclogistics network optimizationgraph neural network policy model
Publication Date：2025-10-20
Online Publishing Date：2026-01-16(First online date of this platform, not the publication date of the document)
Pages：5( 2718-2721,2745 )