Multi-Objective Evolutionary Algorithms and Pattern Search Methods for Circuit Design Problems

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dc.creatorBiondi,Tonio
dc.creatorCiccazzo,Angelo
dc.creatorCutello,Vincenzo
dc.creatorAntona,Santo
dc.creatorNicosia,Giuseppe
dc.creatorSpinella,Salvatore
dc.date2006
dc.date.accessioned2024-02-06T12:54:20Z
dc.date.available2024-02-06T12:54:20Z
dc.descriptionThe paper concerns the design of evolutionary algorithms and pattern search methods on two circuit design problems: the multi-objective optimization of an Operational Transconductance Amplifier and of a fifth-order leapfrog filter. The experimental results obtained show that evolutionary algorithms are more robust and effective in terms of the quality of the solutions and computational effort than classical methods. In particular, the observed Pareto fronts determined by evolutionary algorithms has a better spread of solutions with a larger number of nondominated solutions when compared to the classical multi-objective techniques.
dc.formattext/html
dc.identifierhttps://doi.org/10.3217/jucs-012-04-0432
dc.identifierhttps://lib.jucs.org/article/28603/
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/8999
dc.languageen
dc.publisherJournal of Universal Computer Science
dc.relationinfo:eu-repo/semantics/altIdentifier/eissn/0948-6968
dc.relationinfo:eu-repo/semantics/altIdentifier/pissn/0948-695X
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsJ.UCS License
dc.sourceJUCS - Journal of Universal Computer Science 12(4): 432-449
dc.subjectevolutionary electronics
dc.subjectmulti-objective optimization
dc.subjectcircuit design problems
dc.subjectevolutionary algorithms
dc.subjectgenetic algorithms
dc.subjectclassical optimization methods
dc.subjectpattern search methods
dc.subjectoperational transconductance amplifier
dc.subjectleapfrog filter
dc.titleMulti-Objective Evolutionary Algorithms and Pattern Search Methods for Circuit Design Problems
dc.typeResearch Article
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