Analysing the effects of combining fitness scaling and inversion in genetic algorithms

Genetic Algorithms in their original form as presented by Holland [10] included four operators selection, reproduction, mutation and inversion. Today most attention is given to selection, crossover and mutation, whereas inversion is rarely used. We compare the effectiveness of an inversion operator in a basic GA, and in a GA using fitness scaling. Results indicate that at higher levels of epistasis inversion is more useful in a basic GA than a GA with fitness scaling.

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