A novel evolutionary algorithm for efficient minimization of expensive black-box functions with assisted-modelling

Yod Tenne, S. W. Armfield

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

4 Scopus citations

Abstract

This work presents a novel algorithm for efficient global minimization of expensive black-box functions. A dedicated evolutionary algorithm is used to handle expensive and discontinuous functions; the EA also utilizes information from local-searches to efficiently bias its domain exploration. To enhance efficiency, the algorithm incorporates a density cluster analysis algorithm and a trust-region derivative-free optimizer. The algorithm performs well both when benchmarked against other candidate algorithms over a wide range of test functions and in a challenging real-world optimization problem.

Original languageEnglish
Title of host publication2006 IEEE Congress on Evolutionary Computation, CEC 2006
Pages3219-3226
Number of pages8
StatePublished - 2006
Externally publishedYes
Event2006 IEEE Congress on Evolutionary Computation, CEC 2006 - Vancouver, BC, Canada
Duration: 16 Jul 200621 Jul 2006

Publication series

Name2006 IEEE Congress on Evolutionary Computation, CEC 2006

Conference

Conference2006 IEEE Congress on Evolutionary Computation, CEC 2006
Country/TerritoryCanada
CityVancouver, BC
Period16/07/0621/07/06

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