Hierarchical two-population genetic algorithm

Abstract

In this paper, an analysis of a hierarchical two-population genetic algorithm (2PGA) is presented. Our hierarchical 2PGA composes of two populations that constitute of similarly fit chromosomes. The smaller population, i.e. the elite population, consists of the best chromosomes, whereas the larger population contains less fit chromosomes. The populations have different characteristics, such as size and mutation probability, based on the fitness of the chromosomes in these populations. The performance of our 2PGA is compared to that of a single population genetic algorithm (SPGA). Because the 2PGA has multiple parameters, the significance and the effect of the parameters is also studied. Experimental results show that the 2PGA outperforms the SPGA very reliably without increasing the amount of fitness function evaluations.