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An Enhanced Whale Optimization Algorithm with Simplex Method

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Intelligent Computing Theories and Application (ICIC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11643))

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Abstract

This paper proposes an enhanced whale optimization algorithm with the simplex method named SMWOA algorithm. SMWOA make WOA faster, more robust, and avoid premature convergence. The simplex method (SM) iteratively optimizes the current worst step size, avoids the population search at the edge, and improves the convergence accuracy and speed of the algorithm. The SMWOA algorithm is compared with other well-known meta-heuristic algorithms on 5 benchmarks and 1 classical engineering design problem. The experimental results show that the SMWOA algorithm has better performance than other meta-heuristic optimization algorithms in low and high dimensions.

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Acknowledgment

This work is supported by National Science Foundation of China under Grant No. 61563008. Project of Guangxi University for Nationalities Science Foundation under Grant No. 2018GXNSFAA138146.

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Authors and Affiliations

  1. College of Information Science and Engineering, Guangxi University for Nationalities, Nanning, 530006, China

    Yanbiao Niu, Zhonghua Tang, Yongquan Zhou & Zhongmin Wang

  2. Guangxi High School Key Laboratory of Complex System and Computational Intelligence, Nanning, 530006, China

    Yanbiao Niu, Zhonghua Tang, Yongquan Zhou & Zhongmin Wang

Authors
  1. Yanbiao Niu
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  2. Zhonghua Tang
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  3. Yongquan Zhou
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  4. Zhongmin Wang
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Corresponding author

Correspondence to Yongquan Zhou .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Polytechnic University of Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, NSW, Australia

    Prashan Premaratne

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Niu, Y., Tang, Z., Zhou, Y., Wang, Z. (2019). An Enhanced Whale Optimization Algorithm with Simplex Method. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science(), vol 11643. Springer, Cham. https://doi.org/10.1007/978-3-030-26763-6_70

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  • DOI: https://doi.org/10.1007/978-3-030-26763-6_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26762-9

  • Online ISBN: 978-3-030-26763-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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