Toward a more Generalized Quantum-Inspired Evolutionary Algorithm for Combinatorial Optimization Problems

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dc.contributor.authorAlegría Reymer, Julio Manuel
dc.contributor.authorTúpac Valdivia, Yván Jesús
dc.date.accessioned2019-01-29T22:19:51Z
dc.date.available2019-01-29T22:19:51Z
dc.date.issued2017
dc.description.abstractIn this paper, a generalization of the original Quantum-Inspired Evolutionary Algorithm (QIEA): the Generalized Quantum-Inspired Evolutionary Algorithm (GQIEA) is proposed. Like QIEA, GQIEA is also based on the quantum computing principle of superposition of states, but extending it not only to be used for binary values {0, 1}, but for any finite set of values {1,?, n}. GQIEA, as any other quantum inspired evolutionary algorithm, defines an own quantum individual, an evaluation function and population operators. As in QIEA, GQIEA also defines a generalized Q-gate operator, which is a variation operator to drive the individuals toward better solutions. To demonstrate its effectiveness and applicability, the proposal will be applied to the Knapsack Problem (KP), a classic combinatorial optimization problem. Results show that GQIEA has a good performance even with a small population. © 2015 IEEE.es_PE
dc.description.uriTrabajo de investigaciónes_PE
dc.identifier.doihttps://doi.org/10.1109/SCCC.2013.30es_PE
dc.identifier.isbnurn:isbn:9781509004263es_PE
dc.identifier.issn15224902es_PE
dc.identifier.urihttps://hdl.handle.net/20.500.12590/15804
dc.language.isoenges_PE
dc.publisherIEEE Computer Societyes_PE
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85011891484&doi=10.1109%2fSCCC.2013.30&partnerID=40&md5=7d43b7bddcd73c084de3fc5c64b1e468es_PE
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_PE
dc.sourceRepositorio Institucional - UCSPes_PE
dc.sourceUniversidad Católica San Pabloes_PE
dc.sourceScopuses_PE
dc.subjectCombinatorial optimizationes_PE
dc.subjectOptimizationes_PE
dc.subjectQuantum computerses_PE
dc.subjectQuantum theoryes_PE
dc.subjectCombinatorial optimization problemses_PE
dc.subjectEvaluation functiones_PE
dc.subjectKnap-sack problemes_PE
dc.subjectKnapsack problemses_PE
dc.subjectPrinciple of superpositiones_PE
dc.subjectQuantum Computinges_PE
dc.subjectQuantum inspired evolutionary algorithmes_PE
dc.subjectVariation operatores_PE
dc.subjectEvolutionary algorithmses_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.02.00es_PE
dc.titleToward a more Generalized Quantum-Inspired Evolutionary Algorithm for Combinatorial Optimization Problemses_PE
dc.typeinfo:eu-repo/semantics/conferenceObject
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