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Crossing genetic and swarm intelligence algorithms to generate logic circuits

dc.contributor.authorReis, Cecília
dc.contributor.authorMachado, J. A. Tenreiro
dc.date.accessioned2014-04-04T10:37:31Z
dc.date.available2014-04-04T10:37:31Z
dc.date.issued2009
dc.description.abstractGenetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and genetic. The basic concept of GAs is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. On the other hand, Particle swarm optimization (PSO) is a population based stochastic optimization technique inspired by social behavior of bird flocking or fish schooling. PSO shares many similarities with evolutionary computation techniques such as GAs. The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. PSO is attractive because there are few parameters to adjust. This paper presents hybridization between a GA algorithm and a PSO algorithm (crossing the two algorithms). The resulting algorithm is applied to the synthesis of combinational logic circuits. With this combination is possible to take advantage of the best features of each particular algorithm.por
dc.identifier.doi10400.22/4307
dc.identifier.issn1109-2750
dc.identifier.urihttp://hdl.handle.net/10400.22/4307
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherWorld Scientific and Engineering Academy and Society (WSEAS)por
dc.relation.ispartofseriesWSEAS Transactions on Computers; Vol. 8, Issue 9
dc.relation.publisherversionhttp://www.wseas.us/e-library/transactions/computers/2009/29-631.pdfpor
dc.subjectArtificial intelligencepor
dc.subjectComputational intelligencepor
dc.subjectEvolutionary computationpor
dc.subjectGenetic algorithmspor
dc.subjectParticle swarm optimizationpor
dc.subjectDigital circuitspor
dc.titleCrossing genetic and swarm intelligence algorithms to generate logic circuitspor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage1428por
oaire.citation.issueIssue 9por
oaire.citation.startPage1419por
oaire.citation.titleWSEAS Transactions on Computerspor
oaire.citation.volumeVol. 8por
person.familyNameReis
person.familyNameTenreiro Machado
person.givenNameCecília
person.givenNameJ. A.
person.identifier.ciencia-id7A18-4935-5B29
person.identifier.orcid0000-0001-6131-4677
person.identifier.orcid0000-0003-4274-4879
person.identifier.ridM-2173-2013
person.identifier.scopus-author-id55989030100
rcaap.rightsopenAccesspor
rcaap.typearticlepor
relation.isAuthorOfPublication8128af5d-07d3-4b24-944d-30fde21ae59b
relation.isAuthorOfPublication82cd5c17-07b6-492b-b3e3-ecebdad1254f
relation.isAuthorOfPublication.latestForDiscovery82cd5c17-07b6-492b-b3e3-ecebdad1254f

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