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A bumble bees mating optimization algorithm for global unconstrained optimization problems

Marinakis Ioannis, Matsatsinis Nikolaos, Marinaki Magdalini

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URIhttp://purl.tuc.gr/dl/dias/65E8F3E9-92B4-4790-9972-926EB6E5ED7F-
Identifierhttps://doi.org/10.1007/978-3-642-12538-6_26-
Languageen-
TitleA bumble bees mating optimization algorithm for global unconstrained optimization problemsen
CreatorMarinakis Ioannisen
CreatorΜαρινακης Ιωαννηςel
CreatorMatsatsinis Nikolaosen
CreatorΜατσατσινης Νικολαοςel
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 ItemΠερίληψη Δημοσίευσης σε Συνέδριοel
Type of ItemConference Paper Abstracten
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-28-
Date of Publication2010-
Bibliographic CitationY. Marinakis, M. Marinaki and N. Matsatsinis, “A Bumble bees mating optimization algorithm for global unconstrained optimization problems”, in Nature Inspired Cooperative Strategies for Optimization, Studies in Computational Intelligence, 2010, pp. 305-318. doi: 10.1007/978-3-642-12538-6_26en

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