Divided Range Genetic Algorithms in Multiobjective Optimization Problems
نویسندگان
چکیده
In this paper, Divided Range Genetic Algorithm in Multi objective optimization Problems (DRGA) is proposed. In this method, population of GAs is sorted with respect to the objective function and divided into sub populations. In this model, the Pareto optimum solutions which are close to each other are collected by one sub population. Therefore, by this algorithm, the calculation efficiency is increased, and the neighborhood search can be performed. Through the numerical examples, the followings are made cleared . DRGA is very suitable GA model for parallel processing. DRGA can derive the good solutions compared to the single population model and the distributed model.
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