Optimization methods

Date	31/08/2007
Author	F. Moussouni, S. Brisset and P. Brochet
Affiliation	L2EP – EC Lille – France
Email	fouzia.moussouni@ec-lille.fr
Method	Non-Dominated Sorting Genetic Algorithms (NSGA-II)
References	[1] F. Moussouni, S. Brisset, P. Brochet, “Some results on design of brushless DC wheel motor using SQP and GA”, International Journal of Applied Electromagnetics and Mechanics I.J.A.E.M. Issue: vol. 26, Num 3-4/2007, P. 233-241
Description of the method	NSGA-II is one of the most efficient multi-objective evolutionary algorithms using elitist approach. Its particular fitness assignment scheme consists in sorting the population in different fronts using the non-domination order relation. Then, to form the next generation, the algorithm combines the current population and its offspring generated with the standard bimodal crossover and polynomial operators. Finally, the best individuals in terms of non-dominance and diversity are chosen. This new version of NSGA has a low time complexity of O(N logN), where N is the population size.

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