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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