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Improving SHADE with a Linear Reduction P Value and a Random Jumping Strategy

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Advanced Intelligent Computing Technology and Applications (ICIC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14086))

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Abstract

DE/current-to-pbest/1 is a novel mutation scheme introduced in the JADE algorithm, and is inherited by the famous JADE variant, SHADE. Thereafter, it has continued to be used in various JADE and SHADE variants. Considering the parameter ‘p’ in mutation operator DE/current-to-pbest/1 controls the greediness of mutation directly, this paper adopts a linear reduction strategy of ‘p’ during the evolution process under the framework of SHADE algorithm (LRP-SHADE), and then helps to further trade off the exploration and exploitation abilities. Meanwhile, a random jumping strategy is also adopted, assisting the population to jump out the local optima and keep evolving. Finally, to verify the effectiveness of the proposed LRP-SHADE algorithm, groups of experiments have been conducted on benchmark CEC2014, including both a step-by-step validation experiment for strategies and performance comparisons between LRP-SHADE and other peer algorithms. According to the experimental results, the efficiency and effectiveness of the LRP-SHADE algorithm have been confirmed.

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Author information

Authors and Affiliations

  1. School of Computer Science and Information Engineering, Hubei University, Wuhan, China

    Yanyun Zhang & Li Cheng

  2. Informatization Office, China University of Geosciences, Wuhan, 430074, China

    Guangyu Chen

Authors
  1. Yanyun Zhang
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  2. Guangyu Chen
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  3. Li Cheng
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Corresponding authors

Correspondence to Guangyu Chen or Li Cheng .

Editor information

Editors and Affiliations

  1. Eastern Institute of Technology, Zhejiang, China

    De-Shuang Huang

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

    Prashan Premaratne

  3. Zhengzhou University of Light Industry, Zhengzhou, China

    Baohua Jin

  4. Zhong Yuan University of Technology, Zhengzhou, China

    Boyang Qu

  5. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  6. Department of Computer Science, Liverpool John Moores University, Liverpool, UK

    Abir Hussain

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Zhang, Y., Chen, G., Cheng, L. (2023). Improving SHADE with a Linear Reduction P Value and a Random Jumping Strategy. In: Huang, DS., Premaratne, P., Jin, B., Qu, B., Jo, KH., Hussain, A. (eds) Advanced Intelligent Computing Technology and Applications. ICIC 2023. Lecture Notes in Computer Science, vol 14086. Springer, Singapore. https://doi.org/10.1007/978-981-99-4755-3_5

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  • DOI: https://doi.org/10.1007/978-981-99-4755-3_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-4754-6

  • Online ISBN: 978-981-99-4755-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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