Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/27232

TitleModified constrained differential evolution for solving nonlinear global optimization problems
Author(s)Azad, Md. Abul Kalam
Fernandes, Edite Manuela da G. P.
KeywordsNonlinear programming
Global optimization
Constraints handling
Differential evolution
Issue date2013
PublisherSpringer Verlag
JournalStudies in Computational Intelligence
Abstract(s)Nonlinear optimization problems introduce the possibility of multiple local optima. The task of global optimization is to find a point where the objective function obtains its most extreme value while satisfying the constraints. Some methods try to make the solution feasible by using penalty function methods, but the performance is not always satisfactory since the selection of the penalty parameters for the problem at hand is not a straightforward issue. Differential evolution has shown to be very efficient when solving global optimization problems with simple bounds. In this paper, we propose a modified constrained differential evolution based on different constraints handling techniques, namely, feasibility and dominance rules, stochastic ranking and global competitive ranking and compare their performances on a benchmark set of problems. A comparison with other solution methods available in literature is also provided. The convergence behavior of the algorithm to handle discrete and integer variables is analyzed using four well-known mixed-integer engineering design problems. It is shown that our method is rather effective when solving nonlinear optimization problems.
TypeConference paper
URIhttp://hdl.handle.net/1822/27232
ISBN78-3-642-35637-7
978-3-642-35638-4
DOI10.1007/978-3-642-35638-4_7
ISSN1860-949X
Publisher versionhttp://link.springer.com/chapter/10.1007/978-3-642-35638-4_7
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Livros e capítulos de livros/Books and book chapters

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