Study Of The Logistic Distribution Routing Problem Based On Improved Ant Colony Algorithm

The logistic distribution routing problem is a typical combinatorial optimization problem,it is part of the NP-complete problems.It takes on more computational complexity. At present, there is a lack of any algorithm to find its exact solution in definite polynomial time, the approximate solution as far as possible close exact solution is found out only in reasonable running time .Ant colony algorithm is a new heuristic searching algorithm,it have the advantages of intelligent search, global optimization, robustness, positive feedback.It has been successfully applied to solving the route optimization and a series of combinatorial optimization problems.Ant colony algorithm solving the logistic distribution routing problem is prone to prematurity, stagnation and local optimum. In order to overcome this defect ,a mixed algorithm of MAX-MIN ant system , chaos and mutation is proposed.In the simulation experiments, the MAX-MIN ant algorithm, the mixed algorithm of MAX-MIN ant system and chaos , the mixed algorithm of MAX-MIN ant system and mutation A , the mixed algorithm of MAX-MIN ant system ,chaos and mutation A are respectively adopted to solve the EIL22 problem in Solomon's instances. In the context of meeting the logistic distribution constraints ,the optimal results are 420km,409km,413km and 399km.The simulation results and example computations show that the mixed algorithm of MAX-MIN ant system ,chaos or mutation is effective.The mixed algorithm of MAX-MIN ant system ,chaos and mutation is better to enhance the global optimization capacity of ant colony algorithm , as well as achieves better result for the logistic distribution routing problem.