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>A combination of genetic algorithm and particle swarm optimization method for solving traveling salesman problem
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A combination of genetic algorithm and particle swarm optimization method for solving traveling salesman problem
Traveling salesman problem (TSP) is a well-established NP-complete problem and many evolutionary techniques like particle swarm optimization (PSO) are used to optimize existing solutions for that. PSO is a method inspired by the social behavior of birds. In PSO, each member will change its position in the search space, according to personal or social experience of the whole society. In this paper, we combine the principles of PSO and crossover operator of genetic algorithm to propose a heuristic algorithm for solving the TSP more efficiently. Finally, some experimental results on our algorithm are applied in some instances in TSPLIB to demonstrate the effectiveness of our methods which also show that our algorithm can achieve better results than other approaches.
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