Initiation of Evolutionary Algorithms

Adrian O'Connor; Junbin Gao; John Louis

Initiation of Evolutionary Algorithms

Adrian O'Connor, Junbin Gao, John Louis

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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Abstract

EvolutionaryÂ AlgorithmsÂ areÂ aÂ relativelyÂ recentÂ introductionÂ toÂ theÂ fieldÂ ofÂ optimizationÂ [1],Â [2].Â Â TheyÂ areÂ robustÂ andÂ ableÂ toÂ solveÂ problemsÂ thatÂ wouldÂ otherwiseÂ beÂ difficultÂ orÂ impossibleÂ toÂ solveÂ usingÂ calculusÂ orÂ otherÂ gadientÂ basedÂ methods.Â Â TheÂ terminationÂ criteriaÂ forÂ evolutionaryÂ algorithmsÂ [4]Â areÂ importantÂ considerationsÂ [3].Â Â KnowingÂ whenÂ anÂ evolutionaryÂ algorithmÂ hasÂ doneÂ allÂ itÂ canÂ do,Â whetherÂ thatÂ beÂ convergenceÂ toÂ aÂ solution,Â stalling,Â orÂ deceleration,Â allowsÂ oneÂ toÂ defineÂ rulesÂ thatÂ identifyÂ suchÂ situationsÂ andÂ directÂ theÂ algorithmÂ toÂ actÂ accordingly.Â Â Â

Original language	English
Title of host publication	WORLDCOMP'09
Subtitle of host publication	World Congress in Computer Science, Computer Engineering, and Applied Computing
Place of Publication	USA
Publisher	CSREA Press
Pages	73-78
Number of pages	6
ISBN (Electronic)	1601321066
Publication status	Published - 2009
Event	International Conference on Genetic and Evolutionary Methods (GEM) - Las Vegas Nevada, USA, New Zealand Duration: 13 Jul 2009 → 16 Jul 2009

Conference

Conference	International Conference on Genetic and Evolutionary Methods (GEM)
Country/Territory	New Zealand
Period	13/07/09 → 16/07/09

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@inproceedings{1b9f4f843380455bbbe5b572ae9caaa1,

title = "Initiation of Evolutionary Algorithms",

abstract = "Evolutionary{\^A} Algorithms{\^A} are{\^A} a{\^A} relatively{\^A} recent{\^A} introduction{\^A} to{\^A} the{\^A} field{\^A} of{\^A} optimization{\^A} [1],{\^A} [2].{\^A} {\^A} They{\^A} are{\^A} robust{\^A} and{\^A} able{\^A} to{\^A} solve{\^A} problems{\^A} that{\^A} would{\^A} otherwise{\^A} be{\^A} difficult{\^A} or{\^A} impossible{\^A} to{\^A} solve{\^A} using{\^A} calculus{\^A} or{\^A} other{\^A} gadient{\^A} based{\^A} methods.{\^A} {\^A} The{\^A} termination{\^A} criteria{\^A} for{\^A} evolutionary{\^A} algorithms{\^A} [4]{\^A} are{\^A} important{\^A} considerations{\^A} [3].{\^A} {\^A} Knowing{\^A} when{\^A} an{\^A} evolutionary{\^A} algorithm{\^A} has{\^A} done{\^A} all{\^A} it{\^A} can{\^A} do,{\^A} whether{\^A} that{\^A} be{\^A} convergence{\^A} to{\^A} a{\^A} solution,{\^A} stalling,{\^A} or{\^A} deceleration,{\^A} allows{\^A} one{\^A} to{\^A} define{\^A} rules{\^A} that{\^A} identify{\^A} such{\^A} situations{\^A} and{\^A} direct{\^A} the{\^A} algorithm{\^A} to{\^A} act{\^A} accordingly.{\^A} {\^A} {\^A}",

keywords = "Open access version available, Class{\^A} A{\^A} solutions, Class{\^A} B{\^A} solutions, Evolutionary{\^A} algorithms, SSE, Stochastic{\^A} Funnel{\^A} Algorithm, TSS",

author = "Adrian O'Connor and Junbin Gao and John Louis",

note = "Imported on 03 May 2017 - DigiTool details were: publisher = USA: CSREA Press, 2009. editor/s (773b) = Hamid R Arabnia, Ashu M G Solo (Eds ):; Event dates (773o) = July 13-16, 2009; Parent title (773t) = International Conference on Genetic and Evolutionary Methods (GEM).; International Conference on Genetic and Evolutionary Methods (GEM) ; Conference date: 13-07-2009 Through 16-07-2009",

year = "2009",

language = "English",

pages = "73--78",

booktitle = "WORLDCOMP'09",

publisher = "CSREA Press",

}

TY - GEN

T1 - Initiation of Evolutionary Algorithms

AU - O'Connor, Adrian

AU - Gao, Junbin

AU - Louis, John

N1 - Imported on 03 May 2017 - DigiTool details were: publisher = USA: CSREA Press, 2009. editor/s (773b) = Hamid R Arabnia, Ashu M G Solo (Eds ):; Event dates (773o) = July 13-16, 2009; Parent title (773t) = International Conference on Genetic and Evolutionary Methods (GEM).

PY - 2009

Y1 - 2009

N2 - EvolutionaryÂ AlgorithmsÂ areÂ aÂ relativelyÂ recentÂ introductionÂ toÂ theÂ fieldÂ ofÂ optimizationÂ [1],Â [2].Â Â TheyÂ areÂ robustÂ andÂ ableÂ toÂ solveÂ problemsÂ thatÂ wouldÂ otherwiseÂ beÂ difficultÂ orÂ impossibleÂ toÂ solveÂ usingÂ calculusÂ orÂ otherÂ gadientÂ basedÂ methods.Â Â TheÂ terminationÂ criteriaÂ forÂ evolutionaryÂ algorithmsÂ [4]Â areÂ importantÂ considerationsÂ [3].Â Â KnowingÂ whenÂ anÂ evolutionaryÂ algorithmÂ hasÂ doneÂ allÂ itÂ canÂ do,Â whetherÂ thatÂ beÂ convergenceÂ toÂ aÂ solution,Â stalling,Â orÂ deceleration,Â allowsÂ oneÂ toÂ defineÂ rulesÂ thatÂ identifyÂ suchÂ situationsÂ andÂ directÂ theÂ algorithmÂ toÂ actÂ accordingly.Â Â Â

AB - EvolutionaryÂ AlgorithmsÂ areÂ aÂ relativelyÂ recentÂ introductionÂ toÂ theÂ fieldÂ ofÂ optimizationÂ [1],Â [2].Â Â TheyÂ areÂ robustÂ andÂ ableÂ toÂ solveÂ problemsÂ thatÂ wouldÂ otherwiseÂ beÂ difficultÂ orÂ impossibleÂ toÂ solveÂ usingÂ calculusÂ orÂ otherÂ gadientÂ basedÂ methods.Â Â TheÂ terminationÂ criteriaÂ forÂ evolutionaryÂ algorithmsÂ [4]Â areÂ importantÂ considerationsÂ [3].Â Â KnowingÂ whenÂ anÂ evolutionaryÂ algorithmÂ hasÂ doneÂ allÂ itÂ canÂ do,Â whetherÂ thatÂ beÂ convergenceÂ toÂ aÂ solution,Â stalling,Â orÂ deceleration,Â allowsÂ oneÂ toÂ defineÂ rulesÂ thatÂ identifyÂ suchÂ situationsÂ andÂ directÂ theÂ algorithmÂ toÂ actÂ accordingly.Â Â Â

KW - Open access version available

KW - ClassÂ AÂ solutions

KW - ClassÂ BÂ solutions

KW - EvolutionaryÂ algorithms

KW - SSE

KW - StochasticÂ FunnelÂ Algorithm

KW - TSS

M3 - Conference paper

SP - 73

EP - 78

BT - WORLDCOMP'09

PB - CSREA Press

CY - USA

T2 - International Conference on Genetic and Evolutionary Methods (GEM)

Y2 - 13 July 2009 through 16 July 2009

ER -

Initiation of Evolutionary Algorithms

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