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Fast Convergent Spider Monkey Optimization Algorithm

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Proceedings of Sixth International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 546))

Abstract

Spider Monkey Optimization (SMO) is a recent optimization method, which has drawn interest of researchers in different areas because of its simplicity and efficiency. This paper presents an effort to modify Spider Monkey Optimization Algorithm with higher exploitation capabilities. A new acceleration coefficient based strategy is proposed in the basic version of SMO. The proposed algorithm is named as Fast Convergent Spider Monkey Optimization Algorithm (FCSMO). FCSMO is tested over 14 benchmark test functions and compared with basic SMO. The result reveals that FCSMO will surely become a good variant of SMO.

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Authors and Affiliations

  1. Rajasthan Technical University, Kota, India

    Neetu Agarwal & S. C. Jain

Authors
  1. Neetu Agarwal
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  2. S. C. Jain
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Corresponding author

Correspondence to Neetu Agarwal .

Editor information

Editors and Affiliations

  1. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, India

    Kusum Deep

  2. Department of Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

  3. Department of Mathematics, National Institute of Technology, Silchar, Silchar, Assam, India

    Kedar Nath Das

  4. School of Mathematics, Thapar Institute of Engineering and Technology University, Patiala, Punjab, India

    Arvind Kumar Lal

  5. School of Mathematics, Thapar University Patiala, Patiala, Punjab, India

    Harish Garg

  6. Department of Mathematics and Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya K. Nagar

  7. Department of Applied Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, India

    Millie Pant

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Agarwal, N., Jain, S.C. (2017). Fast Convergent Spider Monkey Optimization Algorithm. In: Deep, K., et al. Proceedings of Sixth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 546. Springer, Singapore. https://doi.org/10.1007/978-981-10-3322-3_5

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  • DOI: https://doi.org/10.1007/978-981-10-3322-3_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3321-6

  • Online ISBN: 978-981-10-3322-3

  • eBook Packages: EngineeringEngineering (R0)

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