Dynamic traveling salesman problem based on evolutionary computation

Huang, Zhijian; Hu, Xiaolin; Chen, Si-Duo

doi:10.1109/cec.2001.934338

Cited by 12 publications

(1 citation statement)

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“…A lot of algorithms have been proposed to solve TSP [3][4][5][6][7][8]. Some of them (based on dynamic programming or branch and bound methods) provide the global optimum solution.…”

Section: Introductionmentioning

confidence: 99%

Orthogonal Genetic Algorithm and its Application in Traveling Salesman Problem

Liu

Yan

2012

AEF

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Abstract. The traveling salesman problem (TSP) is one of the most widely studied NP-hard combinatorial optimization problems. Its statement is deceptively simple, and yet it remains one of the most challenging problems and traditional genetic algorithm trapped into the local minimum easily for solving this problem. Therefore, based on a simple genetic algorithm and combine the base ideology of orthogonal test then applied it to the population initialization, crossover operator, as well as the introduction of adaptive orthogonal local search to prevent local convergence to form a new orthogonal genetic algorithm. The new algorithm shows great efficiency in solving TSP with the problem scale under 300 under the experiment results analyze.

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“…A lot of algorithms have been proposed to solve TSP [3][4][5][6][7][8]. Some of them (based on dynamic programming or branch and bound methods) provide the global optimum solution.…”

Section: Introductionmentioning

confidence: 99%