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Efficient Evolutionary Approach to Approximate the Pareto Optimal Set in Multiobjective Optimization, UPS-EMOA
Dept. of Mathematical Information Technology, University of Jyväskylä.
Department of Mathematical Information Technology, University of Jyväskylä.
2010 (English)In: Optimization Methods and Software, ISSN 1055-6788, E-ISSN 1029-4937, Vol. 25, no 6, 841-858 p.Article in journal (Refereed) Published
Abstract [en]

Solving real-life engineering problems requires often multiobjective, global, and efficient (in terms of objective function evaluations) treatment. In this study, we consider problems of this type by discussing some drawbacks of the current methods and then introduce a new population-based multiobjective optimization algorithm UPS-EMOA which produces a dense (not limited to the population size) approximation of the Pareto-optimal set in a computationally effective manner.

Place, publisher, year, edition, pages
Taylor & Francis, 2010. Vol. 25, no 6, 841-858 p.
Keyword [en]
efficient Pareto-optimal set approximation; multicriteria optimization; population-based approaches; Pareto-optimality; non-dominance; EMO
National Category
Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-73976ISI: 000280772200002OAI: oai:DiVA.org:kth-73976DiVA: diva2:489130
Note
QC 20120210Available from: 2012-02-10 Created: 2012-02-02 Last updated: 2017-12-08Bibliographically approved

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