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A hybrid bumble bees mating optimization - GRASP algorithm for clustering

Marinaki Magdalini, Marinakis Ioannis, Matsatsinis Nikolaos

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URIhttp://purl.tuc.gr/dl/dias/7B83B3FB-5C70-4DF5-8AD0-531E7FF09F0E-
Identifierhttps://doi.org/10.1007/978-3-642-02319-4_66-
Languageen-
TitleA hybrid bumble bees mating optimization - GRASP algorithm for clusteringen
CreatorMarinaki Magdalinien
CreatorΜαρινακη Μαγδαληνηel
CreatorMarinakis Ioannisen
CreatorΜαρινακης Ιωαννηςel
CreatorMatsatsinis Nikolaosen
CreatorΜατσατσινης Νικολαοςel
PublisherAkademie věd Česk� republiky, N�rodohospod�řsk� �staven
Content SummaryA new hybrid algorithm for clustering, which is based on the concepts of the Bumble Bees Mating Optimization (BBMO) and Greedy Randomized Adaptive Search Procedure (GRASP), is presented in this paper. The proposed algorithm is a two phase algorithm which combines a new algorithm called Bumble Bees Mating Optimization algorithm for the solution of the feature selection problem and a GRASP algorithm for the solution of the clustering problem. The performance of the algorithm is compared with other popular metaheuristic and nature inspired methods using datasets from the UCI Machine Learning Repository. The high performance of the proposed algorithm is achieved as the algorithm gives very good results and in some instances the percentage of the correct clustered samples is very high and is larger than 98%.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 Publication2009-
Bibliographic CitationY. Marinakis, M. Marinaki and N. Matsatsinis, “A Hybrid Bumble Bees Mating Optimization – GRASP Algorithm for Clustering”,in 4th International Conference of Hybrid Artificial Intelligence Systems, 2009, Salamanca, pp. 549-556. doi: 10.1007/978-3-642-02319-4_66 el

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