A Parallel Genetic Algorithm to Coevolution of the Strategic Evolutionary Parameters
نویسندگان
چکیده
The strategic choice of parameters (crossover rate, mutation rate, population size, number of generations, among others) in an AG has a direct impact the success of evolutionary search. Therefore the definition of good values in the parameters of evolution can optimize the search process population, finding better solutions in shorter times. Thus a process of self-adaptation constitutes an implicit search with in strategic parameters. Considering the characteristics of evolutionary models and their inherent parallelism, this paper presents a coevolutionary algorithm developed in parallel MPI in order to evolve the parameters of a Multidimensional Knapsack Problem from the evolving capacities of individuals.
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