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dc.contributor.authorMirjalili, SeyedAli
dc.contributor.authorMohd Hashim, Siti Zaiton
dc.date.accessioned2018-07-04T01:30:27Z
dc.date.available2018-07-04T01:30:27Z
dc.date.issued2012
dc.date.modified2013-06-17T04:21:51Z
dc.identifier.issn20103700
dc.identifier.urihttp://hdl.handle.net/10072/48627
dc.description.abstractRecently, the behavior of natural phenomena has become one the most popular sources for researchers in to design optimization algorithms. One of the recent heuristic optimization algorithms is Magnetic Optimization Algorithm (MOA) which has been inspired by magnetic field theory. It has been shown that this algorithm is useful for solving complex optimization problems. The original version of MOA has been introduced in order to solve the problems with continuous search space, while there are many problems owning discrete search spaces. In this paper, the binary version of MOA named BMOA is proposed. In order to investigate the performance of BMOA, four benchmark functions are employed, and a comparative study with Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is provided. The results indicate that BMOA is capable of finding global minima more accurate and faster than PSO and GA.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent1581442 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherInternational Association of Computer Science & Information Technology Press
dc.publisher.placeSingapore
dc.publisher.urihttp://www.ijmlc.org/show-31-91-1.html
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom204
dc.relation.ispartofpageto208
dc.relation.ispartofissue3
dc.relation.ispartofjournalInternational Journal of Machine Learning and Computing
dc.relation.ispartofvolume2
dc.rights.retentionY
dc.subject.fieldofresearchNeural, Evolutionary and Fuzzy Computation
dc.subject.fieldofresearchArtificial Intelligence and Image Processing
dc.subject.fieldofresearchcode080108
dc.subject.fieldofresearchcode0801
dc.titleBMOA: Binary Magnetic Optimization Algorithm
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.rights.copyright© 2012 IJMLC. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
gro.date.issued2012
gro.hasfulltextFull Text
gro.griffith.authorMirjalili, Seyedali


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