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Genetic algorithm includes some parameters that should be adjusting so thatthe algorithm can provide positive results. Crossover operators play veryimportant role by constructing competitive Genetic Algorithms (GAs). In thispaper, the basic conceptual features and specific characteristics of variouscrossover operators in the context of the Traveling Salesman Problem (TSP) arediscussed. The results of experimental comparison of more than six differentcrossover operators for the TSP are presented. The experiment results show thatOX operator enables to achieve a better solutions than other operators tested.

A Comparative Study of Adaptive Crossover Operators for Genetic Algorithms to Resolve the Traveling Salesman Problem