Genetic algorithms and traveling salesman problems

Genetic algorithms and traveling salesman problems

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Article ID: iaor1999975
Country: Netherlands
Volume: 93
Issue: 3
Start Page Number: 490
End Page Number: 510
Publication Date: Sep 1996
Journal: European Journal of Operational Research
Authors: , ,
Keywords: genetic algorithms
Abstract:

A genetic algorithm (GA) with an asexual reproduction plan through a generalized mutation for an evolutionary operator is developed that can be directly applied to a permutation of n numbers for an approximate global optimal solution of a traveling salesman problem. Schema analysis of the algorithm shows that asexual reproduction with the generalized mutation operator preserves the global convergence property of a genetic algorithm thus establishing the fundamental theorem of the GA for the algorithm. Avoiding an intermediate step of encoding through random keys to preserve crossover or permuting n and using ‘fixing’ states for legal crossover are the chief benefits of the innovations reported in this paper. The algorithm has been applied to a number of natural and artificial problems and the results are encouraging.

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