Multiobjective design optimization of electric machine by using genetic algorithm with aggressive species diversity

Yusuke Tsurumi, Shinji Wakao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the design optimization of electric machine, there is a strong need to comprehend in detail the tradeoff relationships among the various objective functions. Therefore, it is important to obtain the sufficiently diverse pareto solutions for appropriately designing electric machine. However, the conventional genetic algorithm (GA) doesn't necessarily find out the diverse pareto solutions. In this paper, we propose a GA with new concept of crowding distance which enables us to obtain the sufficiently diverse pareto solution. Some numerical examples which demonstrate the validity of the proposed method is presented.

Original languageEnglish
Title of host publicationDigests of the 2010 14th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2010
DOIs
Publication statusPublished - 2010 Jul 26
Event14th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC2010 - Chicago, IL, United States
Duration: 2010 May 92010 May 12

Publication series

NameDigests of the 2010 14th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2010

Conference

Conference14th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC2010
CountryUnited States
CityChicago, IL
Period10/5/910/5/12

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Multiobjective design optimization of electric machine by using genetic algorithm with aggressive species diversity'. Together they form a unique fingerprint.

  • Cite this

    Tsurumi, Y., & Wakao, S. (2010). Multiobjective design optimization of electric machine by using genetic algorithm with aggressive species diversity. In Digests of the 2010 14th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2010 [5481748] (Digests of the 2010 14th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2010). https://doi.org/10.1109/CEFC.2010.5481748