库存不足条件下车辆路径问题及其改进PSO算法 3

分析并构建了库存不足条件下车辆路径问题的数学模型;在模型的求解上,提出一种基于子群协作的动态粒子群算法;最后通过算例实验表明:该算法能有效克服标准粒子群算法迭代寻优时选择步长的盲目性,也改善了算法求解时容易陷入局部最优、导致早熟的缺陷,具有较强的全局寻优能力,收敛速度快,计算精度高.

Vehicle routine problem under the condition of stock shortage and its improved PSO algorithm

Abstract: This paper analyzed and established mathematic models for vehicle routine p roblem under the con2 dition of stock shortage. To solve the models, it p resented a dynamic particle swarm op timization algorithm based on sub2group collaboration. Finally, the paper made some experimental calculations, and the results of calculations p roved that the algorithm could avoid blind search effectively, and overcome the limitation of easily trapp ing in local extreme points and leading to p remature, as a result, it had better capability of global op timization, higher speed of convergence and p recision than standard particle swarm op timization.