A new efficient and useful robust optimization approach - Design for multi-objective six sigma

Koji Shimoyama, Akira Oyama, Kozo Fujii

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

35 Citations (Scopus)

Abstract

An efficient and useful robust optimization approach, design for multi-objective six sigma (DFMOSS), has been developed. The DFMOSS couples the ideas of design for six sigma (DFSS) and multi-objective genetic algorithm (MOGA) to solve drawbacks of DFSS; DFMOSS obtains trade-off solutions between optimality and robustness in one optimization. In addition, it does not need careful parameter tuning. Robust optimizations of a test function and welded beam design problem demonstrated that DFMOSS is more effective and more useful than DFSS.

Original languageEnglish
Title of host publication2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings
Pages950-957
Number of pages8
Volume1
Publication statusPublished - 2005 Oct 31
Externally publishedYes
Event2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005 - Edinburgh, Scotland, United Kingdom
Duration: 2005 Sep 22005 Sep 5

Other

Other2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005
CountryUnited Kingdom
CityEdinburgh, Scotland
Period05/9/205/9/5

ASJC Scopus subject areas

  • Engineering(all)

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