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Hybrid Metaheuristic Algorithms: Past, Present, and Future

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Book cover Recent Advances in Swarm Intelligence and Evolutionary Computation

Part of the book series: Studies in Computational Intelligence ((SCI,volume 585))

Abstract

Hybrid algorithms play a prominent role in improving the search capability of algorithms. Hybridization aims to combine the advantages of each algorithm to form a hybrid algorithm, while simultaneously trying to minimize any substantial disadvantage. In general, the outcome of hybridization can usually make some improvements in terms of either computational speed or accuracy. This chapter surveys recent advances in the area of hybridizing different algorithms. Based on this survey, some crucial recommendations are suggested for further development of hybrid algorithms.

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Acknowledgments

The work is supported by National Natural Science Foundation of China (NSFC) under grant No. 61473236, 61273367; and Ningbo Science & Technology Bureau (Project No. 2012B10055).

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Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu Province, China

    T. O. Ting & Kaizhu Huang

  2. School of Science and Technology, Middlesex University, The Burroughs, London, NW4 4BT, UK

    Xin-She Yang

  3. Division of Computer Science, The University of Nottingham, Ningbo, Zhejiang Province, China

    Shi Cheng

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  1. T. O. Ting
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  2. Xin-She Yang
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  3. Shi Cheng
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  4. Kaizhu Huang
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Correspondence to T. O. Ting .

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Editors and Affiliations

  1. School of Science and Technology, Middlesex University, London, United Kingdom

    Xin-She Yang

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Ting, T.O., Yang, XS., Cheng, S., Huang, K. (2015). Hybrid Metaheuristic Algorithms: Past, Present, and Future. In: Yang, XS. (eds) Recent Advances in Swarm Intelligence and Evolutionary Computation. Studies in Computational Intelligence, vol 585. Springer, Cham. https://doi.org/10.1007/978-3-319-13826-8_4

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  • DOI: https://doi.org/10.1007/978-3-319-13826-8_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13825-1

  • Online ISBN: 978-3-319-13826-8

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