A NEW GENETIC ALGORITHM APPLIED TO THE TRAVELING SALESMAN PROBLEM

Genetic algorithms can be applied to a wide class of combinatorial optimization problems. In this paper, we propose an efficientgenetic algorithm (GAs) with some innovative features to solve the traveling salesman problem. We propose a new mutation operator called "Mutation by Extended Elimina- tion", a revised order Crossover and an Elite Selection Method. This algorithm is tested on a set of benchmarks from the TSP-LIB and compared with a pre- viously published GA. The results show the efficiency of the algorithm when applied on both the Traveling Salesman Problem and a scheduling problem from the literature.

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