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A Bumble bees mating optimization algorithm for global unconstrained optimization problems

Matsatsinis Nikolaos, Marinakis Ioannis, Marinaki Magdalini

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URIhttp://purl.tuc.gr/dl/dias/22FFFF03-27D0-40D6-A59F-00A85F7ADEC5-
Identifierhttps://doi.org/10.1007/978-3-642-12538-6_26-
Languageen-
TitleA Bumble bees mating optimization algorithm for global unconstrained optimization problemsen
CreatorMatsatsinis Nikolaosen
CreatorΜατσατσινης Νικολαοςel
CreatorMarinakis Ioannisen
CreatorΜαρινακης Ιωαννηςel
CreatorMarinaki Magdalinien
CreatorΜαρινακη Μαγδαληνηel
PublisherSpringer Verlagen
Content SummaryA new nature inspired algorithm, that simulates the mating behavior of the bumble bees, the Bumble Bees Mating Optimization (BBMO) algorithm, is presented in this paper for solving global unconstrained optimization problems. The performance of the algorithm is compared with other popular metaheuristic and nature inspired methods when applied to the most classic global unconstrained optimization problems. The methods used for comparisons are Genetic Algorithms, Island Genetic Algorithms, Differential Evolution, Particle Swarm Optimization, and the Honey Bees Mating Optimization algorithm. A high performance of the proposed algorithm is achieved based on the results obtained.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-21-
Date of Publication2010-
Bibliographic CitationMarinakis, Y., M. Marinaki, N. Matsatsinis, "A Bumble bees mating optimization algorithm for global unconstrained optimization problems", Studies in Computational Intelligence, vol 284, pp. 305-318. 2010. DOI: 10.1007/978-3-642-12538-6en

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