A comparative performance evaluation of evolutionary algorithms for optimal design of three-phase induction motor

The attribute of an induction motor vary with the number of parameters and the performance relationship between the parameters also is implicit. In this paper a multi-objective problem is considered in which three phase squirrel cage induction motor (SCIM) has been designed in such a way that the efficiency is maximized while power density to be minimized simultaneously keeping various constraints in mind. Three well-known single objective methods such as tabu search (TS), simulated annealing (SA) and Genetic algorithm (GA) for comparing Pareto solutions has also been applied. Performance comparison carried out in this paper by performing different numerical experiments. The result shows that NSGA-II outperforms other three for the considered test cases.