Evolutionary algorithms (EA) have been systematically developed to solve mono-objective, multi-objective and many-objective optimization problems. In recent works connected with the Genetic Algorithms (GAs) in the design optimization of Electrical Machinery, it has been observed that GAs locate the global optimum region faster than the conventional direct search optimization techniques. In this paper a study of the NSGA-II algorithm is presented alongside with the optimized design results, obtained in the research work.
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