Sareni, Bruno and Régnier, Jérémi and Roboam, Xavier Comparison of Geometric Optimization Methods with Multiobjective Genetic Algorithms for Solving Integrated Optimal Design Problems. (2005) In: 7th International Conference on Artificial Evolution (EA'05), 26-28 Oct 2005, Lille, France .
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(Document in English)
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Official URL: http://www.lifl.fr/EA2005/
Abstract
In this paper, system design methodologies for optimizing heterogenous power devices in electrical engineering are investigated. The concept of Integrated Optimal Design (IOD) is presented and a simplified but typical example is given. It consists in finding Pareto-optimal configurations for the motor drive of an electric vehicle. For that purpose, a geometric optimization method (i.e the Hooke and Jeeves minimization procedure) associated with an objective weighting sum and a Multiobjective Genetic Algorithm (i.e. the NSGA-II) are compared. Several performance issues are discussed such as the accuracy in the determination of Pareto-optimal configurations and the capability to well spread these solutions in the objective space.
| Item Type: | Conference or Workshop Item (Paper) |
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| Audience (conference): | International conference proceedings |
| Uncontrolled Keywords: | |
| Institution: | French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE) Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE) |
| Laboratory name: | |
| Statistics: | download |
| Deposited On: | 24 Jul 2013 10:01 |
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