Abstract：To improve the efficiency of urban logistics and reduce road congestion, a bi-level programming model is adopted to solve the problem of logistics distribution center location and path optimization. The upper-level model utilizes an improved Adaptive Immune Optimization Algorithm (IAIA) to determine the distribution center locations that minimize costs. Meanwhile, the lower-level model aims to minimize vehicle travel time considering road congestion, improving the Ant Colony Algorithm (IACA), and considering the influence of actual travel speeds on pheromone concentration updates. Through experiments with designed logistics distribution test cases, it is validated that the bi-level programming model, the improved Adaptive Immune Optimization Algorithm, and the enhanced Ant Colony Optimization Algorithm are effective approaches for solving logistics distribution center location and route optimization problems.
万孟然, 叶春明. 基于双层规划的物流配送中心选址及配送优化[J]. 复杂系统与复杂性科学, 2025, 22(4): 118-124.
WAN Mengran, YE Chunming. Location and Routing Optimization of Logistics Distribution Center Based on Bi-level Programming[J]. Complex Systems and Complexity Science, 2025, 22(4): 118-124.
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