Study Of The Optimizing Of Vehicle Routing Problem Based On The Ant Colony Optimization

With the development of computer technology, some new biomimetic optimizing algorithms like the Ant Colony Optimization are developed quickly and applied broadly.In this thesis, we begin with the introduction of Vehicle Routing Problem related topics. Then we introduce the background and the details of Ant Colony Optimization. Among the applications of ACO, we emphasize some existing methods solving sutra VRP problem.The new improvements and results of ACO solving sutra VRP problem are presented, which are the main contributions of the thesis. And we proposed three improvements on ant colony optimization algorithm to solve VRP problem. First, a novel optimized implementing approach is designed to reduce the processing costs involved with routing of ants in the conventional ACO. Secondly, the improvement of ACO is put forward to ant Individual Variation. The experiments show it can avoid stagnation behavior. At last, this paper proposes an adaptive ant colony algorithm for solving the physical distribution Vehicle routing problem which is improved from basic ACO by means of integrating C-W algorithm and introducing the adaptive ant attraction of arc in order to decrease computing time and avoid stagnation behavior. The computational experiments show that this algorithm is feasible and valid for VRP.The improved algorithm greatly improves the performance of ACO, and it gets good effect on applying for large-scale VRP problems. The results of the simulated experiments show that the improved algorithm not only reduces the number of routing in the ACO but also surpasses existing algorithms in performance for solving large-scale VRP problems. And it is obvious to reduce the number of routing with expands of client server'scale. This paper is that we put forward some beneficial suggestion on the solution through analyzed the every parameter in the function of solution.