基于变异和动态自适应PSO的物流配送中心选址模型

Location Model of Logistics Distribution Center Based on Variation and Dynamic Adaptive PSO

在考虑到各影响因素,建立了总成本最少、满足时效性的物流配送中心选址模型。针对该复杂性较高的实际优化问题,提出了一种带变异和动态自适应的粒子群算法来求解,对算法中的参数进行非线性动态自适应调整,同时移植了遗传算法的变异机制帮助算法有效摆脱局部最优的束缚,结果表明基于双重机制优化的粒子群算法,算法效率和寻优能力有了进一步的提升。提出的算法应用于比较复杂的物流配送中心选址问题求解,亦有出色的表现。

Taking into account various influencing factors,this study established a logistics distribution center location model with the least total cost and the best timeliness.A particle swarm optimization with variation and dynamic self-adjustment is proposed to solve the complex practical optimization problem.The parameters in the algorithm are adjusted dynamically and non-linearly.At the same time,the variation mechanism with transplanted genetic algorithm helps the algorithm effectively get rid of the constraints of local optimization.The results show that the particle swarm optimization based on dual mechanism optimization has further improved the algorithm efficiency and optimization ability.The proposed algorithm is applied to the solution of the more complex logistics distribution center location problem,and it also has outstanding practical performance.