A local multiobjective optimization algorithm using neighborhood field

Zhou Wu, Tommy W. S. Chow

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

19 Citations (Scopus)

Abstract

A new local search algorithm for multiobjective optimization problems is proposed to find the global optima accurately and diversely. This paper models the cooperatively local search as a potential field, which is called neighborhood field model (NFM). Using NFM, a new Multiobjective Neighborhood Field Optimization (MONFO) algorithm is proposed. In MONFO, the neighborhood field can drive each individual moving towards the superior neighbor and away from the inferior neighbor. MONFO is compared with other popular multiobjective algorithms under twelve test functions. Intensive simulations show that MONFO is able to deliver promising results in the respects of accuracy and diversity, especially formultimodal problems. © Springer-Verlag 2012.
Original languageEnglish
Pages (from-to)853-870
JournalStructural and Multidisciplinary Optimization
Volume46
Issue number6
DOIs
Publication statusPublished - Dec 2012

Research Keywords

  • Contour gradient optimization
  • Evolutionary algorithms
  • Local search
  • Multiobjective neighborhood field optimization
  • Multiobjective optimization
  • Neighborhood field model

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