A new mechanism for maintaining diversity of Pareto archive in multi-objective optimization

The article introduces a new mechanism for selecting individuals to a Pareto archive. It was combined with a micro-genetic algorithm and tested on several problems. The ability of this approach to produce individuals uniformly distributed along the Pareto set without negative impact on convergence i...

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Bibliographic Details
Published inAdvances in engineering software (1992) Vol. 41; no. 7; pp. 1031 - 1057
Main Authors Hajek, Jaroslav, Szoelloes, Andras, Aaistek, Jakub
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.07.2010
Subjects
Algorithms
Archives
Computer programs
Convergence
Diversity
Micro-genetic algorithm
Multi-objective optimization
Optimization
Packages
Pareto archive
Pareto optimality
Software
Software engineering
Multi-objective optimization
Micro-genetic algorithm
Pareto archive
Diversity
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Summary:The article introduces a new mechanism for selecting individuals to a Pareto archive. It was combined with a micro-genetic algorithm and tested on several problems. The ability of this approach to produce individuals uniformly distributed along the Pareto set without negative impact on convergence is demonstrated on presented results. The new concept was confronted with NSGA-II, SPEA2, and IBEA algorithms from the PISA package. Another studied effect is the size of population versus number of generations for small populations.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0965-9978
DOI:10.1016/j.advengsoft.2010.03.003