Haploid Versus Diploid Genetic Algorithms. A Comparative Study

Genetic algorithms (GAs) are powerful tools for solving complex optimization problems, usually using a haploid representation. In the past decades, there has been a growing interest concerning the diploid genetic algorithms. Even though this area seems to be attractive, it lacks wider coverage and research in the Evolutionary Computation community. The scope of this paper is to provide some reasons why this situation happens and in order to fulfill this aim, we present experimental results using a conventional haploid GA and a developed diploid GA tested on some major benchmark functions used for performance evaluation of genetic algorithms. The obtained results show the superiority of the diploid GA over the conventional haploid GA in the case of the considered benchmark functions.