Adaptive Parameter Control Using Search State Estimation and Extreme Individuals for Differential Evolution-Reference-Cited by-同舟云学术

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Adaptive Parameter Control Using Search State Estimation and Extreme Individuals for Differential Evolution

Published:2024-04-01 Issue:0 Volume:2024 Page:60-67
ISSN:2188-4730
Container-title:Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
language:en
Short-container-title:Stochastic Systems Theory and its Applications (SSS)

Author:

Takahama Tetsuyuki¹,Sakai Setsuko²

Affiliation:

1. Department of Intelligent Systems, Hiroshima City University

2. Faculty of Commercial Sciences, Hiroshima Shudo University

Publisher

The Institute of Systems, Control and Information Engineers

Link

https://www.jstage.jst.go.jp/article/sss/2024/0/2024_60/_pdf

Reference27 articles.

1. [1] A. E. Babalola, B. A. Ojokoh, and J. B. Odili, “A review of population-based optimization algorithms,” in 2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS), 2020, pp.1–7.

2. [2] A. E. Eiben and J. E. Smith, What Is an Evolutionary Algorithm? Berlin, Heidelberg: Springer Berlin Heidelberg, 2015, pp.25–48.

3. [3] R. Storn and K. Price, “Differential evolution –A simple and efficient heuristic for global optimization over continuous spaces,” Journal of Global Optimization, vol.11, pp.341–359, 1997.

4. [4] J. Kennedy and R. C. Eberhart, Swarm Intelligence. San Francisco: Morgan Kaufmann, 2001.

5. [5] J. Zhang and A. C. Sanderson, “JADE: Adaptive differential evolution with optional external archive,” IEEE Transactions on Evolutionary Computation, vol.13, no.5, pp.945–958, Oct. 2009.

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