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Enhancing the Local Search Ability of the Brain Storm Optimization Algorithm by Covariance Matrix Adaptation

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Brain Storm Optimization Algorithms

Part of the book series: Adaptation, Learning, and Optimization ((ALO,volume 23))

Abstract

Recently, the Brain Storm Optimization (BSO) algorithm has attracted many researchers and practitioners attention from the evolutionary computation community. However, like many other population based algorithms, BSO shows good performance at global exploration but not good enough at local exploitation. To alleviate this issue, in this chapter, the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is utilized in the Global-best BSO (GBSO), with the aim to combine the exploration ability of BSO and local ability of CMA-ES and to design an improved version of BSO. The performance of the proposed algorithm is tested by solving 28 classical optimization problems and the proposed algorithm is shown to perform better than GBSO.

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Author information

Authors and Affiliations

  1. Faculty of Computer and Informatics, Zagazig University, Zagazig, Egypt

    Seham Elsayed

  2. American University of Kuwait, Salmiya, Kuwait

    Mohammed El-Abd

  3. UNSW, Canberra, Australia

    Karam Sallam

  4. Zagazig University, Zagazig, Egypt

    Karam Sallam

Authors
  1. Seham Elsayed
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  2. Mohammed El-Abd
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  3. Karam Sallam
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Corresponding author

Correspondence to Seham Elsayed .

Editor information

Editors and Affiliations

  1. School of Computer Science, Shaanxi Normal University, Xi’an, China

    Shi Cheng

  2. Shenzhen Key Laboratory of Computational Intelligence, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

Appendix

Appendix

The benchmark problems solved in this chapter can be found in the following link: Classical optimization problems.

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Elsayed, S., El-Abd, M., Sallam, K. (2019). Enhancing the Local Search Ability of the Brain Storm Optimization Algorithm by Covariance Matrix Adaptation. In: Cheng, S., Shi, Y. (eds) Brain Storm Optimization Algorithms. Adaptation, Learning, and Optimization, vol 23. Springer, Cham. https://doi.org/10.1007/978-3-030-15070-9_5

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