Comparing the performances of six nature-inspired algorithms on a real-world discrete optimization problem

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dc.contributor.authorHakli, Huseyin
dc.contributor.authorUguz, Harun
dc.contributor.authorOrtacay, Zeynep
dc.date.accessioned2024-02-23T13:43:53Z
dc.date.available2024-02-23T13:43:53Z
dc.date.issued2022
dc.departmentNEÜen_US
dc.description.abstractMany new, nature-inspired optimization algorithms are proposed these days, and these algorithms are gaining popularity day by day. These algorithms are frequently preferred for these real-world problems as they need less information, are reliable and robust, and have a structure that can easily be applied to discrete problems. Too many algorithms result in difficulty choosing the correct technique for the problem, and selecting an unwise method affects the solution quality. In addition, some algorithms cannot be reliable for some specific real-world problems but very successful for others. In order to guide and give insight into the practitioners and researchers about this problem, studies involving the comparison and evaluation of the performance of algorithms are needed. In this study, the performances of six nature-inspired methods, which included five new implementations of differential evolutionary algorithms (DE), scatter search (SS), equilibrium optimizer (EO), marine predators algorithm (MPA), and honey badger algorithm (HBA) applied to land redistribution problem and genetic algorithms (GA), were compared. In order to compare the algorithms in detail, various performance indicators were used as problem based and algorithm based. Experimental results showed that DE and SS algorithms have a more successful performance than the other methods by solution quality, robustness, and many problem-based indicators.en_US
dc.identifier.doi10.1007/s00500-022-07466-1
dc.identifier.endpage11667en_US
dc.identifier.issn1432-7643
dc.identifier.issn1433-7479
dc.identifier.issue21en_US
dc.identifier.scopus2-s2.0-85137847521en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage11645en_US
dc.identifier.urihttps://doi.org/10.1007/s00500-022-07466-1
dc.identifier.urihttps://hdl.handle.net/20.500.12452/10963
dc.identifier.volume26en_US
dc.identifier.wosWOS:000852938800001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofSoft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDifferential Evolution Algorithmen_US
dc.subjectScatter Searchen_US
dc.subjectDiscrete Optimizationen_US
dc.subjectComparisonen_US
dc.subjectNature-Inspired Algorithmsen_US
dc.titleComparing the performances of six nature-inspired algorithms on a real-world discrete optimization problemen_US
dc.typeArticleen_US

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