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Hybrid Gravitational Search and Clonal Selection Algorithm for Global Optimization

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Advances in Swarm Intelligence (ICSI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7929))

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Abstract

In recent years, there has been a growing interest in algorithms inspired by the behaviors of natural phenomena. However, the performance of any single pure algorithm is limited by the size and complexity of the problem. To further improve the search effectiveness and solution robustness, hybridization of different algorithms is a promising research direction. In this paper, we propose a hybrid iteration algorithm by combing the gravitational search algorithm with the clonal selection. The gravitational search performs exploration in the search space, while the clonal selection is implemented to carry out exploitation within the neighborhood of the solutio found by gravitational search. The emerged hybrid algorithm, called GSCSA, thus reasonably combines the characteristics of both base algorithms. Experimental results based on several benchmark functions demonstrate the superiority of the proposed algorithm in terms of solution quality and convergence speed.

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Author information

Authors and Affiliations

  1. College of Information Science and Technology, Donghua University, China

    Shangce Gao, Hongjian Chai & Beibei Chen

  2. School of Information, Renmin University of China, China

    Gang Yang

Authors
  1. Shangce Gao
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  2. Hongjian Chai
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  3. Beibei Chen
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  4. Gang Yang
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), School of lectronics Engineering and Computer Science, Department of Machine Intelligence, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, 215123, Suzhou, China

    Yuhui Shi

  3. Automation College, Harbin Engineering University, 150001, Harbin, China

    Hongwei Mo

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© 2013 Springer-Verlag Berlin Heidelberg

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Gao, S., Chai, H., Chen, B., Yang, G. (2013). Hybrid Gravitational Search and Clonal Selection Algorithm for Global Optimization. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38715-9_1

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  • DOI: https://doi.org/10.1007/978-3-642-38715-9_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38714-2

  • Online ISBN: 978-3-642-38715-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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