Real-coded evolutionary algorithms with parentcentric recombination

Abstract

Due to an increasing interest in solving real-world optimization problems using evolutionary algorithms (EAs), researchers have developed a number of real-parameter genetic algorithms (GAs) in the recent past. In such studies, the main research effort is spent on developing an efficient recombination operator. Such recombination operators use probability distributions around the parent solutions to create offspring. Some operators emphasize solutions at the center of mass of parents and some around the parents. We propose a generic parent-centric recombination operator (PCX) and compare its performance with a couple of commonly-used mean-centric recombination operators (UNDX and SPX). With the help of a steady-state, elite-preserving, and computationally fast EA model, simulation results show the superiority of PCX on three test problems.