中文摘要：

物流配送路径优化问题是一类实用价值很高的NP组合问题,针对传统启发式优化算法搜索速度慢、易陷入局部最优解的缺点,本文提出了一种自适应变异粒子群算法,该算法在迭代过程中加入了变异操作,根据群体适应度方差调整变异概率的大小,并通过调整惯性权重因子来增强算法跳出局部最优的能力.本文将自适应变异粒子群算法应用于物流配送路径问题优化,建立数学模型,介绍该算法的详细实现过程.将该算法通过和遗传算法、混合蚁群算法和标准粒子群算法进行比较,证明了其搜索速度和寻优能力的优越性.

英文摘要：

The logistics distribution route problem is a kind of NP combination problem which possesses important practical value.In order to overcome the problems such as long computing time and easy to fall into local best for traditional heuristic optimization algorithm,an Adaptive Mutation Particle Swarm Optimization（AMPSO） is proposed.The algorithm adds mutation operation in iteration process and adjusts the inertia weighting factor to enhance its ability to break away from local optimum,and the mutation probability is adjusted by variance of the population＇s fitness.In this paper,the algorithm of AMPSO is investigated to solve the logistics distribution route problem,and the mathematic mode is established and the solution algorithm is developed.The simulation results of example indicate that AMPSO has more search speed and stronger optimization ability than that of genetic algorithm（GA）,hybrid ant colony algorithm and the PSO algorithm.