Efficiency determination of induction motors using multi-objective evolutionary algorithms

Authors:
Mehmet Çunkaş;Tahir Sağ
Affiliations:
Dept. of Electronics and Computer Education, Faculty of Technical Education, Selçuk University, 42003 Konya, Turkey;Dept. of Electronics and Computer Education, Faculty of Technical Education, Selçuk University, 42003 Konya, Turkey
Venue:
Advances in Engineering Software
Year:
2010

Citing 4
Cited 0

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A tool for multiobjective evolutionary algorithms

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Abstract

This paper introduces a method based on multi-objective evolutionary algorithms for the determination of in-service induction motor efficiency. In general, the efficiency is determined by accumulating multiple objectives into one objective by a linear combination and optimizing the resulting single-objective problem. The approach has some drawbacks such that exact information about solution alternatives will not be readily visible. In this paper the multi-objective evolutionary optimization algorithms, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Strength Pareto Evolutionary Algorithm-2 (SPEA2), are successfully applied to the efficiency determination problem in induction motor. The performances of algorithms are compared on the basis of the obtained results.