An Improved Swarm Intelligence Algorithm for Solving TSP Problem

Traveling Salesman Problem (TSP) is a typical NP-Complete problem. This paper, through finding the solution of TSP, combining the use of high-efficiency gene regulatory algorithm , particle swarm optimization and ant colony optimization, proposes a kind of improved swarm intelligence algorithm GRPSAC. The GRPSAC overcomes the disadvantages of several algorithms through the use of the crossover, the mutation and the gene regulation. The experimental results indicate that GRPSAC not only has a highefficiency, but also induces better optimal results

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