Hybrid real-coded genetic algorithms with female and male differentiation

Parent-centric real-parameter crossover operators create the offspring in the neighborhood of one of the parents, the female parent, using a probability distribution. The other parent, the male one, defines the range of this probability distribution. The female and male differentiation process determines the individuals in the population that may become female or/and male parents. An important property of this process is that it makes possible the design of two kinds of real-coded genetic algorithms: ones that promote global search and ones that are effective local searchers. In this paper, we study the performance of a hybridization of these real-coded genetic algorithms when tackling the test problems proposed for the Special Session on Real-Parameter Optimization of the IEEE Congress on Evolutionary Computation 2005