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Large-Scale Global Optimization via Swarm Intelligence

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Book cover Solving Computationally Expensive Engineering Problems

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 97))

Abstract

Large-scale global optimization (LSGO) is a challenging task with many scientific and engineering applications. Complexity, nonlinearity and size of the problems are the key factors that pose significant challenges in solving such problems. Though the main aim of optimization is to obtain the global optimal solutions with the least computational costs, it is impractical in most applications. Thus, a practical approach is to search for suboptimal solutions and good solutions, which may not be easily achievable for large-scale problems. In this chapter, the challenges posed by LSGO are addressed, followed by some potential strategies to overcome these difficulties. We also discuss some challenging topics for further research.

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Acknowledgements

This work was carried out at the International Doctoral Innovation Centre (IDIC). The authors acknowledge the financial support from Ningbo Education Bureau, Ningbo Science and Technology Bureau, China’s MOST and The University of Nottingham. The work is also partially supported by National Natural Science Foundation of China (NSFC) under grant No.60975080, 61273367; and Ningbo Science & Technology Bureau (Project No.2012B10055).

Author information

Authors and Affiliations

  1. International Doctoral Innovation Centre, The University of Nottingham, Ningbo, People’s Republic of China

    Shi Cheng

  2. Division of Computer Science, The University of Nottingham, Ningbo, People’s Republic of China

    Shi Cheng

  3. Department of Electrical & Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, People’s Republic of China

    T. O. Ting

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

    Xin-She Yang

Authors
  1. Shi Cheng
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  2. T. O. Ting
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  3. Xin-She Yang
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Corresponding author

Correspondence to Shi Cheng .

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Editors and Affiliations

  1. Engineering Optimization & Modeling Center, School of Science & Engineering, Reykjavik University, Reykjavik, Iceland

    Slawomir Koziel

  2. Engineering Optimization & Modeling Center, School of Science & Engineering, Reykjavik University, Reykjavik, Iceland

    Leifur Leifsson

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

    Xin-She Yang

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Cheng, S., Ting, T.O., Yang, XS. (2014). Large-Scale Global Optimization via Swarm Intelligence. In: Koziel, S., Leifsson, L., Yang, XS. (eds) Solving Computationally Expensive Engineering Problems. Springer Proceedings in Mathematics & Statistics, vol 97. Springer, Cham. https://doi.org/10.1007/978-3-319-08985-0_10

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