A fast robust optimization methodology based on polynomial chaos and evolutionary algorithm for inverse problems

Siu Lau Ho, Shiyou Yang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

26 Citations (Scopus)


This paper explores the potential of polynomial chaos in robust designs of inverse problems. A fast numerical methodology based on combinations of polynomial chaos expansion and evolutionary algorithm is reported in this study. With the proposed methodology, polynomial chaos expansion is used as a stochastic response surface model for efficient computations of the expectancy metric of the objective function. Additional enhancements, such as the introduction of a new methodology for expected fitness assignment and probability feasibility model, a novel driving mechanism to bias the next iterations to search for both global and robust optimal solutions, are introduced. Numerical results on two case studies are reported to illustrate the feasibility and merits of the present work.
Original languageEnglish
Article number6136632
Pages (from-to)259-262
Number of pages4
JournalIEEE Transactions on Magnetics
Issue number2
Publication statusPublished - 1 Feb 2012


  • Evolutionary algorithm
  • polynomial chaos expansion
  • robust design
  • robust optimization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

Cite this