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