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Issue title: OIPE 2006
Article type: Research Article
Authors: Moussouni, F.a; * | Brisset, S.a | Brochet, P.a
Affiliations: [a] L2EP, Ecole Centrale de Lille, Cité Scientifique, BP 48, 59651 Villeneuve d'Ascq, France
Correspondence: [*] Corresponding author. E-mail: Fouzia.moussouni@ec-lille.fr
Abstract: The sequential quadratic programming and genetic algorithms are finely tuned on the optimal design of a brushless DC wheel motor. Combining both methods, a hybrid approach is tested. Multiobjective optimizations are performed using Nondominated Sorting Genetic Algorithm, Strength Pareto Evolutionary Algorithm, and a variable weighted sum of objectives with the sequential quadratic programming. The Pareto fronts are compared in term of accuracy, uniformity, and coverage criteria using some quality indicators.
Keywords: Sequential quadratic programming, genetic algorithms, mixed-integer optimization, multiobjective optimization
DOI: 10.3233/JAE-2007-913
Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 26, no. 3-4, pp. 233-241, 2007
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