Evolutionary search of optimal concepts using a relaxed-pareto-optimality approach

Elad Denenberg, Amiram Moshaiov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study is motivated by the need to support concept selection under conflicting objectives. A recent idea concerning concept-based relaxed-Pareto-optimality is employed to develop a "soft" evolutionary search approach.The proposed method allows set-based conceptual solutions,with performances close to those of the concept-based Paretooptimal set, to survive the evolutionary search process. This allows designers, which are engaged in concept selection to examine not only the Pareto-optimal solutions from the different concepts. The relaxed-optimality exposes, within a desired performance resolution, other particular solutions of interest in concept selection. The proposed numerical solution approach involves a modification of NSGA-II to meet the needs of solving the described problem. The suggested algorithm is demonstrated using both an academic test function and aconceptual path planning problem.

Original languageEnglish
Title of host publication2009 IEEE Congress on Evolutionary Computation, CEC 2009
PublisherIEEE Computer Society
Pages2524-2531
Number of pages8
ISBN (Print)9781424429592
DOIs
StatePublished - 2009
Event2009 IEEE Congress on Evolutionary Computation, CEC 2009 - Trondheim, Norway
Duration: 18 May 200921 May 2009

Publication series

Name2009 IEEE Congress on Evolutionary Computation, CEC 2009

Conference

Conference2009 IEEE Congress on Evolutionary Computation, CEC 2009
Country/TerritoryNorway
CityTrondheim
Period18/05/0921/05/09

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