An improved ant colony algorithm based on fusion mutation search solves the traveling salesman problem
Aiming at the problems of slow convergence and local optimality of ant colony algorithms,an improved ant colony algorithm based on fusion mutation search was proposed.In the pheromone initialization stage,the nearest neighbor operator was used to construct the initial path for each ant,and the best 10%path was selected for pheromone initialization.In the iterative pro-cess,the mutation operation of genetic algorithm is used for reference,and the mutation search is added.Two operators,2-opt and heuristic insertion,are selected to search the mutation of ant paths respectively,and the pheromone is updated after merging and optimizing.The simulation results of TSPLIB show that the convergence speed and optimization ability of the improved algorithm are improved effectively.
ant colony algorithmTSPnearest neighbor operator2-optheuristic insertion
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