In order to find a better way to solve the Vehicle Routing Problem ,this paper puts forward a new way. In this paper combines Artificial Fish Swarm Algorithm and Tabu Search Algorithm to solve the Vehicle Routing Problem, at first use Artificial Fish Swarm Algorithm to get the phase solution as the initial solution of Tabu Search Algorithm, and then get the best solution of the problem by Tabu Search Algorithm.Experiments show this has a good search ability to Vehicle Routing Problem.
Hybrid multi-objective particle swarm algorithm is applied to vehicle routing problem and achieved good results, this paper based on the previous work, dynamic inertia weight is added to the particle swarm algorithm with intelligence factors, it improved the global search ability and the capacity of local convergence of the particle swarm algorithm; and the idea of immunity is introduced in the algorithm ,which makes the hybrid multi-objective particle swarm algorithm can effectively discard the repeated solutions in solving vehicle routing problems, this operation can improve the efficiency of the algorithm, and obtain better results under the same conditions.
基于改进人工鱼群算法的最短路径问题研究An Modified Artificial Fish Swarm Algorithm for the Optimal Routing Problem
