Abstract
The purpose of the paper is to analyze an incorporation of local search mechanisms into five crossover operators (KPoint, AEX, HGreX, HProX and HRndX) used in genetic algorithms, compare the results depending on various parameters and draw the conclusions. The local search is used randomly with some probability instead of the standard crossover procedure in order to generate a new individual. We analyze injecting the local search in two situations: to resolve the conflicts and also without a conflict with a certain probability. The discussed mechanisms improve the obtained results and significantly accelerate the calculations. Moreover, we show that there exists an optimal degree of the local search component, and it depends on the particular crossover operator.
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Kordos, M., Kulka, R., Steblik, T., Scherer, R. (2022). Local Search in Selected Crossover Operators. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13352. Springer, Cham. https://doi.org/10.1007/978-3-031-08757-8_31
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