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System optimization by multiobjective genetic algorithms and analysis of the coupling between variables, constraints and objectives

Régnier, Jérémi and Sareni, Bruno and Roboam, Xavier System optimization by multiobjective genetic algorithms and analysis of the coupling between variables, constraints and objectives. (2005) COMPEL : The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 24 (3). 805-820. ISSN 0332-1649

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Official URL: http://dx.doi.org/10.1108/03321640510598157

Abstract

This paper presents a methodology based on Multiobjective Genetic Algorithms (MOGA’s) for the design of electrical engineering systems. MOGA’s allow to optimize multiple heterogeneous criteria in complex systems, but also simplify couplings and sensitivity analysis by determining the evolution of design variables along the Pareto-optimal front. A rather simplified case study dealing with the optimal dimensioning of an inverter – permanent magnet motor – reducer – load association is carried out to demonstrate the interest of the approach.

Item Type:Article
Additional Information:Thanks to Emerald editor. The original publication is available at http://www.emeraldinsight.com
HAL Id:hal-00779389
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
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Deposited By: Bruno SARENI
Deposited On:22 Jan 2013 09:49

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