MNEARO: a meta swarm intelligence optimization algorithm for engineering applications

DOI10.1016/J.CMA.2023.116664MaRDI QIDQ6185223

Guo Wei, Feiyang Huang, Kang Chen, Gang Hu

Publication date: 29 January 2024

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

zbMATH Keywords

optimization problemmutation strategyelite opposition-based learning strategyAR optimizationprey identification strategy

Mathematics Subject Classification ID

Biology and other natural sciences (92-XX) Operations research, mathematical programming (90-XX)

Cites Work

• Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: A survey of the state-of-the-art
• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• The arithmetic optimization algorithm
• An enhanced hybrid arithmetic optimization algorithm for engineering applications
• Boosting ant colony optimization via solution prediction and machine learning
• An effective multi-objective artificial hummingbird algorithm with dynamic elimination-based crowding distance for solving engineering design problems
• A self-adaptive hybridized differential evolution naked mole-rat algorithm for engineering optimization problems
• GSA: A gravitational search algorithm
• A comparative study of artificial bee colony algorithm
• Dwarf mongoose optimization algorithm
• MCSA: multi-strategy boosted chameleon-inspired optimization algorithm for engineering applications
• IYDSE: ameliorated Young's double-slit experiment optimizer for applied mechanics and engineering

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