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Analysis Effect of Tournament Selection on Genetic Algorithm Performance in Traveling Salesman Problem (TSP)

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, , Citation S Prayudani et al 2020 J. Phys.: Conf. Ser. 1566 012131 DOI 10.1088/1742-6596/1566/1/012131

1742-6596/1566/1/012131

Abstract

This study discusses effect of tournament selection on the way individuals compete on the performance of Genetic Algorithms so which one tournament selection is most suitable for the Traveling Salesman Problem (TSP). One algorithm in solving TSP is Genetic Algorithm, which has 3 (three) main operators, namely selection, crossover, and mutation. Selection is one of the main operators in the Genetic Algorithm, where select the best individuals who can survive (the shortest travel route). Tournament selection compares a number of individuals through a match to choose the best individual based on each fitness value, so that the winning individual (the individual going to the next generation) will be chosen. There is two way to compete in an individual in tournament selection is by tournament selection with replacement (TSWR) and without replacement (TSWOR). The final results of the study conducted TSWR gets the best fitness, even though the generation that gets the best fitness is reaching the maximum generation (takes longer to get the best fitness).

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10.1088/1742-6596/1566/1/012131