Three-learning strategy particle swarm algorithm for global optimization problems

DOI10.1016/J.INS.2022.01.075OpenAlexW4210505659MaRDI QIDQ6190043

Qiuying Lin, Xin-Ming Zhang

Publication date: 5 February 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2022.01.075

zbMATH Keywords

particle swarm optimizationoptimization algorithmlearning strategyglobal optimization problemsswarm intelligence optimization algorithm

Mathematics Subject Classification ID

Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Nonconvex programming, global optimization (90C26) Approximation methods and heuristics in mathematical programming (90C59)

Cites Work

• A social learning particle swarm optimization algorithm for scalable optimization
• Example-based learning particle swarm optimization for continuous optimization
• An expanded particle swarm optimization based on multi-exemplar and forgetting ability
• Multipopulation cooperative particle swarm optimization with a mixed mutation strategy
• Novel biogeography-based optimization algorithm with hybrid migration and global-best Gaussian mutation
• Gradient-based optimizer: a new metaheuristic optimization algorithm
• Heterogeneous comprehensive learning and dynamic multi-swarm particle swarm optimizer with two mutation operators
• Ranking-based biased learning swarm optimizer for large-scale optimization
• A novel metaheuristic optimizer inspired by behavior of jellyfish in ocean
• Honey badger algorithm: new metaheuristic algorithm for solving optimization problems

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