Piecewise-linear particle swarm optimizer, basic dynamics, reference frame invariance, and search performance-Reference-Cited by-同舟云学术

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Piecewise-linear particle swarm optimizer, basic dynamics, reference frame invariance, and search performance

Published:2022 Issue:2 Volume:13 Page:170-195
ISSN:2185-4106
Container-title:Nonlinear Theory and Its Applications, IEICE
language:en
Short-container-title:NOLTA

Author:

Sasaki Tomoyuki¹^ORCID,Nakano Hidehiro²^ORCID

Affiliation:

1. Shonan Institute of Technology

2. Tokyo City University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Rehabilitation,Physical Therapy, Sports Therapy and Rehabilitation,General Medicine

Link

https://www.jstage.jst.go.jp/article/nolta/13/2/13_170/_pdf

Reference37 articles.

1. [1] X.S. Yang, Nature-Inspired Metaheuristic Algorithms, 2nd Edition, Luniver Press, 2010.

2. [2] J. Kennedy and R.C. Eberhart, “Particle swarm optimization,” Proc. IEEE International Conference on Neural Networks, vol. 4, pp. 1942-1948, 1995.

3. [3] Y. Shi and R.C. Eberhart, “A modified particle swarm optimizer,” Proc. IEEE CEC 1998, pp. 69-73, 1998.

4. [4] D. Karaboga, “An idea based on honey bee swarm for numerical optimization,” Technical Report TR06, Erciyes University Engineering Faculty, Computer Engineering Department, 2005.

5. [5] X.S. Yang, “Cuckoo search via lévy flights,” Proc. NaBic 2009, IEEE Publications, USA, pp. 210-214, 2009.

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