Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/9668

TitleSelf-adaptive penalties in the electromagnetism-like algorithm for constrained global optimization problems
Author(s)Rocha, Ana Maria A. C.
Fernandes, Edite Manuela da G. P.
KeywordsGlobal optimization
Electromagnetism-like algorithm
Penalty technique
Adaptive penalty
Issue date2009
CitationWORLD CONGRESS ON STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 8, Lisbon, Portugal, 2009 – “World Congress on Structural and Multidisciplinary Optimization”. [Lisboa : s.n., 2009].
Abstract(s)A well-known approach for solving constrained optimization problems is based on penalty functions. A penalty technique transforms the constrained problem into an unconstrained problem by penalizing the objective function when constraints are violated and then minimizing the penalty function using methods for unconstrained problems. In this paper, we analyze the implementation of a self-adaptive penalty approach, within the electromagnetism-like population-based algorithm, in which the constraints that are more difficult to be satisfied will have relatively higher penalty values. The penalties depend upon the level of constraint violation scaled by the average of the objective function values. Numerical results obtained with a collection of well-known global optimization problems are presented and a comparison with other stochastic methods is also reported.
TypeConference paper
URIhttp://hdl.handle.net/1822/9668
Peer-Reviewedyes
AccessOpen access
Appears in Collections:LES/ALG - Textos completos em actas de encontros científicos internacionais com arbitragem

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