Compromise Based Evolutionary Multiobjective Optimization Algorithm for Multidisciplinary Optimization

Benoît Guédas (), Xavier Gandibleux () and Philippe Dépincé ()
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Benoît Guédas: École Centrale de Nantes
Xavier Gandibleux: Université de Nantes
Philippe Dépincé: École Centrale de Nantes

Chapter Chapter 6 in New State of MCDM in the 21st Century, 2011, pp 69-78 from Springer

Abstract: Abstract Multidisciplinary Design Optimization deals with engineering problems composed of several sub-problems – called disciplines – that can have antagonist goals and thus require to find compromise solutions. Moreover, the sub-problems are often multiobjective optimization problems. In this case, the compromise solutions between the disciplines are often considered as compromises between all objectives of the problem, which may be not relevant in this context. We propose two alternative definitions of the compromise between disciplines. Their implementations within the well-known NSGA-II algorithm are studied and results are discussed.

Keywords: Compromise solutions; Evolutionary algorithm; Multidisciplinary optimization; Multiobjective optimization; Preferences. (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnechp:978-3-642-19695-9_6

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DOI: 10.1007/978-3-642-19695-9_6

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