Abstract
In this paper, we apply the genetic algorithm and ant colony optimization algorithms, which is a kind of meta-heuristics search algorithm, for the traveling salesman problem. We perform experiments to evaluate which one among these algorithms solves the problem more efficiently by means of the solution quality and the execution time. The experimental results show that the ant colony optimization algorithms are efficient in terms of the solution quality, while the genetic algorithm is efficient in terms of the execution time for large traveling salesman problems
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