Efficiency determination of induction motors using multi-objective evolutionary algorithms

Advances in Engineering Software · Ocak 2010

YÖKSİS Kayıtları

Efficiency determination of induction motors using multi objective evolutionary algorithms

Advances in Engineering Software · 2010 SCI-Expanded

Doç. Dr. TAHİR SAĞ →

Efficiency determination of induction motors using multi objective evolutionary algorithms

Advances in Engineering Software · 2010 SCI-Expanded

Prof. Dr. MEHMET ÇUNKAŞ →

YÖKSİS Kayıtları — ISSN Eşleşmesi

Fast computation of the prime implicants by exact direct cover algorithm based on the new partial ordering operation rule

2011 ISSN: 09659978 SCI-Expanded

Prof. Dr. FATİH BAŞÇİFTÇİ →

10.1016/j.advengsoft.2011.02.009

Cost optimization of feed mixes by genetic algorithms

2009 ISSN: 0965-9978 SCI-Expanded

Prof. Dr. MEHMET ÇUNKAŞ →

10.1016/j.advengsoft.2009.04.003

Efficiency determination of induction motors using multi objective evolutionary algorithms

2010 ISSN: 09659978 SCI-Expanded

Prof. Dr. MEHMET ÇUNKAŞ →

10.1016/j.advengsoft.2009.07.008

A tool for multiobjective evolutionary algorithms

2009 ISSN: 09659978 SCI-Expanded

Prof. Dr. MEHMET ÇUNKAŞ →

10.1016/j.advengsoft.2009.01.001

Efficiency determination of induction motors using multi objective evolutionary algorithms

2010 ISSN: 09659978 SCI-Expanded

Doç. Dr. TAHİR SAĞ →

10.1016/j.advengsoft.2009.07.008

A tool for multiobjective evolutionary algorithms

2009 ISSN: 0965-9978 SCI-Expanded Q3

Doç. Dr. TAHİR SAĞ →

10.1016/j.advengsoft.2009.01.001

Cost optimization of feed mixes by genetic algorithms

2009 ISSN: 0965-9978 SCI-Expanded

Dr. Öğr. Üyesi UĞUR TAŞKIRAN →

10.1016/j.advengsoft.2009.04.003

Makale Bilgileri

Dergi Advances in Engineering Software

ISSN09659978

Yayın TarihiOcak 2010

Cilt / Sayfa41 · 255-261

DOI10.1016/j.advengsoft.2009.07.008

Scopus ID2-s2.0-70449530614

Özet 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. © 2009 Elsevier Ltd. All rights reserved.