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Analysis of Optimization Capability of Selection Operator for DE Algorithm

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Computational Intelligence and Intelligent Systems (ISICA 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 986))

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Abstract

Differential Evolution Algorithm (DE) is an intelligent algorithm widely used in recent years. Many scholars have studied DE algorithm from many aspects, such as theory and application. Selection operator using greedy strategy is an important part of DE algorithm. Traditionally thought, the DE selection operator is only a means to maintain effective population evolution of DE. In fact, the DE selection operator also has some capability to optimize. For this reason, this paper constructs some DE variants, and compares the optimization results of them with the standard DE algorithm. Simulation results show that the new algorithm which only using greedy selection can achieve certain optimization results, meanwhile, DE algorithm which removing its greedy selection operator only has poor performance. This proves that DE selection operator has certain optimization capability.

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Acknowledgements

This work was supported in part by Henan Science and Technology Project (No.182102210411) and Henan University Key Research Project (No.18A520040).

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Authors and Affiliations

  1. College of Information Engineering, Huanghuai University, Zhumadian, 463000, China

    Huichao Liu & Fengying Yang

Authors
  1. Huichao Liu
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  2. Fengying Yang
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Correspondence to Huichao Liu .

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Editors and Affiliations

  1. School of Information Science and Technology, Jiujiang University, Jiujiang, China

    Hu Peng

  2. School of Information Science and Technology, Jiujiang University, Jiujiang, China

    Changshou Deng

  3. School of Computer, Wuhan University, Wuhan, China

    Zhijian Wu

  4. School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Yong Liu

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Liu, H., Yang, F. (2019). Analysis of Optimization Capability of Selection Operator for DE Algorithm. In: Peng, H., Deng, C., Wu, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2018. Communications in Computer and Information Science, vol 986. Springer, Singapore. https://doi.org/10.1007/978-981-13-6473-0_12

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  • DOI: https://doi.org/10.1007/978-981-13-6473-0_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6472-3

  • Online ISBN: 978-981-13-6473-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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