Population Symmetrization in Genetic Algorithms
Grzegorz Kusztelak, Adam Lipowski, Jacek Kucharski · Applied Sciences · 2022
The paper presents a memetic modification of the classical genetic algorithm by introducing a cyclic symmetrization of the population, symmetrizing the parental points around the current population leader. Such an operator provides a more spherical distribution of the population around the current leader, which significantly improves exploitation. The proposed algorithm was described, illustrated by examples, and theoretically analyzed. Its effectiveness was examined using a recognized benchmark, which includes the continuous functions test set on a multidimensional cube, to be minimized.