期刊
INFORMATION PROCESSING LETTERS
卷 103, 期 5, 页码 169-176出版社
ELSEVIER
DOI: 10.1016/j.ipl.2007.03.010
关键词
algorithms; particle swarm optimization; traveling salesman problem; generalized traveling salesman problem; swap operator
A novel particle swarm optimization (PSO)-based algorithm for the traveling salesman problem (TSP) is presented. An uncertain searching strategy and a crossover eliminated technique are used to accelerate the convergence speed. Compared with the existing algorithms for solving TSP using swarm intelligence, it has been shown that the size of the solved problems could be increased by using the proposed algorithm. Another PSO-based algorithm is proposed and applied to solve the generalized traveling salesman problem by employing the generalized chromosome. Two local search techniques are used to speed up the convergence. Numerical results show the effectiveness of the proposed algorithms. (c) 2007 Elsevier B.V. All rights reserved.
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