A league-knock-out tournament quantum particle swarm optimization algorithm for nonlinear constrained optimization problems and applications-Reference-Cited by-同舟云学术

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A league-knock-out tournament quantum particle swarm optimization algorithm for nonlinear constrained optimization problems and applications

Published:2023-01-28 Issue:6 Volume:14 Page:1117-1143
ISSN:1868-6478
Container-title:Evolving Systems
language:en
Short-container-title:Evolving Systems

Author:

Mandal Goutam,Kumar Nirmal,Duary Avijit,Shaikh Ali Akbar^ORCID,Bhunia Asoke Kumar

Funder

University Grants Commission

Department of Science and Technology, Government of West Bengal

Department of Science and Technology, Government of India

Publisher

Springer Science and Business Media LLC

Subject

Control and Optimization,Computer Science Applications,Modeling and Simulation,Control and Systems Engineering

Link

https://link.springer.com/content/pdf/10.1007/s12530-023-09485-1.pdf

Reference100 articles.

1. Abualigah L, Elaziz MA, Yousri D, et al (2022) Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering. J Intell Manuf 1–39

2. Alatas B (2011) ACROA: artificial chemical reaction optimization algorithm for global optimization. Expert Syst Appl 38:13170–13180

3. Amirjanov A (2006) The development of a changing range genetic algorithm. Comput Methods Appl Mech Eng 195:2495–2508

4. Bedolla-Ibarra MG, Cabrera-Hernandez M del C, Aceves-Fernández MA, Tovar-Arriaga S (2022) Classification of attention levels using a Random Forest algorithm optimized with Particle Swarm Optimization. Evol Syst 13:687–702

5. Bellera CA, Julien M, Hanley JA (2010) Normal approximations to the distributions of the Wilcoxon statistics: accurate to what N? Graphical insights. J Stat Educ 18:

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