Khalid  Jebari, Amina  Dik, Abdelaziz  Bouroumi, Aziz  Ettouhami, 
    Combined Crossover Operator,
    Research Journal of Applied Sciences,
    Volume 10,Issue 3,
    2015,
    Pages 75-79,
    ISSN 1815-932x,
    rjasci.2015.75.79,
    (https://makhillpublications.co/view-article.php?doi=rjasci.2015.75.79)
    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.
    Keywords: Evolutionary computation;crossover;genetic algorithms;real coding crossover;CCO