Research Journal of Applied Sciences

Year: 2015
Volume: 10
Issue: 3
Page No. 75 - 79

Combined Crossover Operator

Authors : Khalid Jebari, Amina Dik, Abdelaziz Bouroumi and Aziz Ettouhami

Abstract: Genetic algorithms are optimization and search methods based on the principles of Darwinian evolution and genetics that try to provide the optimal solution of a problem. They evolve a population of candidate solutions to the problem, using mutation, crossover and selection operators. Based on the diversity and the efficiency of four well known crossover operators, this study presents a novel operator called Combined Crossover Operator (CCO). The comparison with those four crossover operators shows that the results obtained by the CCO are promising.

How to cite this article:

Khalid Jebari, Amina Dik, Abdelaziz Bouroumi and Aziz Ettouhami, 2015. Combined Crossover Operator. Research Journal of Applied Sciences, 10: 75-79.

Design and power by Medwell Web Development Team. © Medwell Publishing 2023 All Rights Reserved