Evolutionary Experience-Driven Particle Swarm Optimization with Dynamic Searching

Evolutionary Experience-Driven Particle Swarm Optimization with Dynamic Searching

Particle swarm optimization (PSO) algorithms have been successfully used for various complex optimization problems. However, balancing the diversity and convergence is still a problem that requires continuous research. Therefore, an evolutionary experience-driven particle swarm optimization with dyn...

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Bibliographic Details
Main Authors: Wei Li, Jianghui Jing, Yangtao Chen, Xunjun Chen, Ata Jahangir Moshayedi
Format: Article
Language:English
Published: Tsinghua University Press 2023-12-01
Series:Complex System Modeling and Simulation
Subjects:
particle swarm optimization
experience-based topology structure
elite archive
gaussian crisscross learning
Online Access:https://www.sciopen.com/article/10.23919/CSMS.2023.0015

Internet

https://www.sciopen.com/article/10.23919/CSMS.2023.0015

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