低碳约束下冷链物流配送共享仓选址多目标优化方法

Multi-target optimization method of cold chain logistics distribution shared warehouse location under low-carbon constraint

针对当前冷链物流配送中心选址模型存在选址不合理、选址过程复杂,导致资源浪费和经济成本增加的问题,提出在低碳约束下,构建一个基于低碳约束冷链物流配送共享仓中心选址和路径优化模型,在粒子群算法的基础上,分别加入免疫算法和粒子群算法,得到改进免疫粒子群算法和混合粒子群算法,通过这两种算法分别实现共享仓中心选址求解快速寻优和多目标优化,以提升模型的路径优化能力和鲁棒性。实验结果表明,提出的方法改进免疫粒子群算法可在不同约束条件下实现冷链物流配送共享仓快速选址,且选择位置寻优求解速度提升;同时通过混合粒子群算法可实现物流路径优化,规避路径缺陷,从而提升路径优化能力,实现多目标优化路径的准确选址。

In view of the current cold chain logistics distribution center location model is unreasonable, location process is complex, resource waste and economic cost increase, build a low carbon constraint, based on low carbon constraints cold chain logistics distribution sharing warehouse center site selection and path optimization model, on the basis of improved particle swarm algorithm, add immune algorithm and particle swarm algorithm, improve immune particle swarm algorithm and mixed particle swarm algorithm, through the two algorithms sharing warehouse center location solution fast optimization and multi-target optimization, to improve the path optimization ability and robustness of the model. The experimental results show that the proposed method can realize the rapid location of cold chain logistics distribution under different constraints, and realize the logistics path optimization, avoid path defects, improve the path optimization ability and realize the accurate site selection of multi-objective optimization path.