Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/2299
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dc.contributor.authorRadojičić Matić, Ninaen_US
dc.date.accessioned2025-07-24T07:31:02Z-
dc.date.available2025-07-24T07:31:02Z-
dc.date.issued2017-
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/2299-
dc.description.abstractThis paper considers solving the Max-Min Diversity Problem (MMDP) by using genetic algorithms (GAs). Computational experiments on the smaller benchmark data set showed that the classic GA quickly reached all optimal solutions obtained previously by an exact solver. However, some of larger instances of MMDP were challenging for the classic GA. Although researchers have established the most commonly used parameter setting for GA that has good performance for most of the problems, it is still challenging to choose the adequate values for the parameters of the algorithm. One approach to overcome this is changing parameter values during the --. run. This paper presents a possible implementation of this approach. The genetic algorithm is extended by adding a fuzzy rule formulated from GA experts' knowledge and experience. Short CPU times and high-quality solutions for tested instances indicate that the proposed approach is more suitable for solving the MMDP than the classic GA.en_US
dc.language.isoenen_US
dc.publisherBelgrade : IPSI BgD Internet Research Societyen_US
dc.relation.ispartofIPSI Transactions on Internet Researchen_US
dc.subjectDiscrete optimizationen_US
dc.subjectGenetic algorithmsen_US
dc.subjectParameter settingen_US
dc.subjectFuzzy rulesen_US
dc.titleAn Approach to Solving the Min-Max Diversity Problem Using Genetic Algorithm with Fuzzy Decisionsen_US
dc.typeArticleen_US
dc.identifier.urlhttps://ipsitransactions.org/journals/papers/tir/2017jan/p3.pdf-
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.relation.issn1820-4503en_US
dc.relation.firstpageArticle no. 23-8 (7 pages)en_US
dc.relation.volume13en_US
dc.relation.issue1en_US
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeArticle-
item.cerifentitytypePublications-
crisitem.author.deptInformatics and Computer Science-
crisitem.author.orcid0000-0002-9968-948X-
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