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A Partheno-Genetic Algorithm for Dynamic 0-1 Multidimensional Knapsack Problem

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dc.contributor.authorÜnal, Ali Nadi
dc.contributor.authorKayakutlu, Gülgün
dc.contributor.ituauthorKayakutlu, Gülgün
dc.date.accessioned2026-01-25T03:36:12Z
dc.date.issued2015-10-07
dc.description.abstractSummary: Multidimensional Knapsack problem (MKP) is a well-known, NP-hard combinatorial optimization problem. Several metaheuristics or exact algorithms have been proposed to solve stationary MKP. This study aims to solve this difficult problem with dynamic conditions, testing a new evolutionary algorithm. In the present study, the Partheno-genetic algorithm (PGA) is tested by evolving parameters in time. Originality of the study is based on comparing the performances in static and dynamic conditions. First the effectiveness of the PGA is tested on both the stationary, and the dynamic MKP. Then, the improvements with different random restarting schemes are observed. The PGA achievements are shown in statistical and graphical analysis.
dc.description.urihttps://doi.org/10.1051/ro/2015011
dc.description.urihttps://zbmath.org/6562239
dc.description.urihttps://dx.doi.org/10.1051/ro/2015011
dc.identifier.doi10.1051/ro/2015011
dc.identifier.eissn1290-3868
dc.identifier.endpage66
dc.identifier.issn0399-0559
dc.identifier.openairedoi_dedup___::574141a08d4b64fffa7bb72091735bfd
dc.identifier.orcid0000-0001-8548-6377
dc.identifier.startpage47
dc.identifier.urihttps://hdl.handle.net/11527/44099
dc.identifier.volume50
dc.publisherEDP Sciences
dc.relation.ispartofRAIRO - Operations Research
dc.rightsCLOSED
dc.subjectpartheno-genetic algorithm
dc.subjectCombinatorial optimization
dc.subjectmultidimensional Knapsack problem
dc.subjectdynamic environments
dc.subjectcombinatorial optimization
dc.subjectProblem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
dc.titleA Partheno-Genetic Algorithm for Dynamic 0-1 Multidimensional Knapsack Problem
dc.typeArticle
dspace.entity.typePublication
person.identifier.orcid0000-0001-8548-6377

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