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Tuning an evolutionary algorithm with taguchi methods and application to the dimensioning of an electrical motor

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G. WimmerAuthors Info & Claims

CSTST '08: Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology

Pages 265 - 272

https://doi.org/10.1145/1456223.1456279

Published: 28 October 2008 Publication History

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Abstract

This paper presents an original method of permanent magnet motor optimal design developped by both Electrical Engineering and Computer Science laboratories. An Evolutionary Algorithm combining Genetic Algorithms and Multiagent Systems is used. This Genetic Multiagent System parameters are determined using a robust design method based on the Taguchi approach. The quality of the algorithm is evaluated considering the multiobjective quality of the solutions it delivers on a permanent magnet machine constrained optimization. Contradictory objectives as efficiency and weight have a large influence on the design of electrical machines. Performances of the resulting tuned up algorithm are compared with previous results from the authors.

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Cited By

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Mani NGursaran Sinha AMani A(2014)Taguchi-Based Tuning of Rotation Angles and Population Size in Quantum-Inspired Evolutionary Algorithm for Solving MMDPProceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 201210.1007/978-81-322-1602-5_12(105-111)Online publication date: 26-Feb-2014
https://doi.org/10.1007/978-81-322-1602-5_12
Abdou WBloch CCharlet DSpies FMoore J(2012)Adaptive multi-objective genetic algorithm using multi-pareto-rankingProceedings of the 14th annual conference on Genetic and evolutionary computation10.1145/2330163.2330228(449-456)Online publication date: 7-Jul-2012
https://dl.acm.org/doi/10.1145/2330163.2330228
Abdou WBloch CCharlet DSpies F(2012)Multi-Pareto-Ranking evolutionary algorithmProceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization10.1007/978-3-642-29124-1_17(194-205)Online publication date: 11-Apr-2012
https://dl.acm.org/doi/10.1007/978-3-642-29124-1_17

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Tuning an evolutionary algorithm with taguchi methods and application to the dimensioning of an electrical motor

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Published In

CSTST '08: Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology

October 2008

733 pages

ISBN:9781605580463

DOI:10.1145/1456223

Conference Chair:
Lotfi A. Zadeh
University of California
,
General Chairs:
Youakim Badr
INSA-Lyon, France
,
Ajith Abraham
Norwegian University of Science and Technology, Norway
,
Yukio Ohsawa
Tokyo Institute of Technology, Japan
,
Program Chairs:
Richard Chbeir
University of Bourgogne, France
,
Fernando Ferri
IRPPS-CNR, Italy
,
Mario Koeppen
Kyushu Institute of Technology, Japan
,
Dominique Laurent
University of Cergy-Pontoise, France

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Association for Computing Machinery

New York, NY, United States

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Published: 28 October 2008

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Cited By

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Mani NGursaran Sinha AMani A(2014)Taguchi-Based Tuning of Rotation Angles and Population Size in Quantum-Inspired Evolutionary Algorithm for Solving MMDPProceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 201210.1007/978-81-322-1602-5_12(105-111)Online publication date: 26-Feb-2014
https://doi.org/10.1007/978-81-322-1602-5_12
Abdou WBloch CCharlet DSpies FMoore J(2012)Adaptive multi-objective genetic algorithm using multi-pareto-rankingProceedings of the 14th annual conference on Genetic and evolutionary computation10.1145/2330163.2330228(449-456)Online publication date: 7-Jul-2012
https://dl.acm.org/doi/10.1145/2330163.2330228
Abdou WBloch CCharlet DSpies F(2012)Multi-Pareto-Ranking evolutionary algorithmProceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization10.1007/978-3-642-29124-1_17(194-205)Online publication date: 11-Apr-2012
https://dl.acm.org/doi/10.1007/978-3-642-29124-1_17

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