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A Hybrid Clustering Algorithm Based on Honey Bees Mating Optimization and Greedy Randomized Adaptive Search Procedure

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Learning and Intelligent Optimization (LION 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5313))

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Abstract

This paper introduces a new hybrid algorithmic nature inspired approach based on the concepts of the Honey Bees Mating Optimization Algorithm (HBMO) and of the Greedy Randomized Adaptive Search Procedure (GRASP), for optimally clustering N objects into K clusters. The proposed algorithm for the Clustering Analysis, the Hybrid HBMO-GRASP, is a two phase algorithm which combines a HBMO algorithm for the solution of the feature selection problem and a GRASP for the solution of the clustering problem. This paper shows that the Honey Bees Mating Optimization can be used in hybrid synthesis with other metaheuristics for the solution of the clustering problem with remarkable results both to quality and computational efficiency. Its performance is compared with other popular stochastic/metaheuristic methods like particle swarm optimization, ant colony optimization, genetic algorithms and tabu search based on the results taken from the application of the methodology to data taken from the UCI Machine Learning Repository.

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Author information

Authors and Affiliations

  1. Decision Support Systems Laboratory, Department of Production Engineering and Management, Technical University of Crete, 73100, Chania, Greece

    Yannis Marinakis & Nikolaos Matsatsinis

  2. Industrial Systems Control Laboratory, Department of Production Engineering and Management, Technical University of Crete, 73100, Chania, Greece

    Magdalene Marinaki

Authors
  1. Yannis Marinakis
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  2. Magdalene Marinaki
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  3. Nikolaos Matsatsinis
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Editor information

Editors and Affiliations

  1. Dept. Computer Science, University of Bologna, Bologna, Italy

    Vittorio Maniezzo

  2. Università degli Studi di Trento, Trento, Italy

    Roberto Battiti

  3. Discrete Math and Complex Systems Department, Sandia National Laboratories, Albuquerque, New Mexico, USA

    Jean-Paul Watson

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Marinakis, Y., Marinaki, M., Matsatsinis, N. (2008). A Hybrid Clustering Algorithm Based on Honey Bees Mating Optimization and Greedy Randomized Adaptive Search Procedure . In: Maniezzo, V., Battiti, R., Watson, JP. (eds) Learning and Intelligent Optimization. LION 2007. Lecture Notes in Computer Science, vol 5313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92695-5_11

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  • DOI: https://doi.org/10.1007/978-3-540-92695-5_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92694-8

  • Online ISBN: 978-3-540-92695-5

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