改进的蚁群算法在物流配送路径问题中的实现

Realization of VRP Based on Improved Ant Colony Algorithm

蚁群算法是受自然界中蚁群搜索食物行为启发而提出的一种智能优化算法,通过介绍蚁群觅食过程中基于信息素的最短路径的搜索策略,以及蚁群算法在TSP问题中的应用,在分析TSP与车辆路径问题(VRP)的异同后,给出用于求解车辆路径问题(VRP)的蚁群算法,并针对蚁群算法在求解过程容易出现过早收敛问题,提出了几种改进算法的措施。最后通过powerbuilder的仿真实现结果表明,这种算法对VRP问题有较好的求解效果。

Ant colony algorithm is an intelligent optimization algorithm derives heuristically from simulating ants to seek food, on the basis of analyzing the difference between TSP and VRP and introducing the application of ACO in TSP and the search strat- egy based on the shortest router with Pheromone in the procedure of seeking food of ants, an improved Ant colony algorithm is proposed to solve VRP. This paper gives some measures to improve the Ant colony algorithm in the procedure to seeking the solution. At last, the experimental results based on Powerbuilder show that this algorithm is extremely robust to solve the optimal solutions of VRP. Its application in VRP has achieved good results.