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Mobile, Ubiquitous, and Intelligent Computing pp 629–636Cite as

Recent Development of Metaheuristics for Clustering

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 274))

Abstract

Metaheuristics have been successfully applied to quite a lot of services, systems, and products frequently found in our daily life. Until now, none of the metaheuristics ever proposed are perfect for all the optimization problems; rather, each algorithm has its pros and cons. Although several high-performance metaheuristics exist, there is still plenty of room to improve the final result they produce and the computation time they take. Since 2001, quite a few number of novel metaheuristics have been developed to provide a better way for solving the optimization problems. A brief review for eight of these novel metaheuristics is given in this paper. To evaluate the performance of these algorithms, we apply them to a well-known combinatorial optimization problem, data clustering, and the results are analyzed and discussed.

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Author information

Authors and Affiliations

  1. Department of Applied Informatics and Multimedia, Chia Nan University of Pharmacy & Science, Tainan, Taiwan

    Chun-Wei Tsai

  2. Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan

    Wei-Cheng Huang & Ming-Chao Chiang

Authors
  1. Chun-Wei Tsai
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  2. Wei-Cheng Huang
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  3. Ming-Chao Chiang
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Corresponding author

Correspondence to Chun-Wei Tsai .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. Biomedical Informatics Neuroscience, Ohio State University Center for Biomedical Engineering, Columbus, Ohio, USA

    Hojjat Adeli

  3. Dept of Computer Education, Jeju National University Teachers College, Jeju Special Self-Governing Province, Korea, Republic of (South Korea)

    Namje Park

  4. Ryerson University Dept. Computer Science, Toronto, Ontario, Canada

    Isaac Woungang

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Tsai, CW., Huang, WC., Chiang, MC. (2014). Recent Development of Metaheuristics for Clustering. In: Park, J., Adeli, H., Park, N., Woungang, I. (eds) Mobile, Ubiquitous, and Intelligent Computing. Lecture Notes in Electrical Engineering, vol 274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40675-1_93

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  • DOI: https://doi.org/10.1007/978-3-642-40675-1_93

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40674-4

  • Online ISBN: 978-3-642-40675-1

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