Enhancing performance of particle swarm optimization through an algorithmic link with genetic algorithms

DOI10.1007/S10589-013-9605-0zbMath1304.90219OpenAlexW2092448443MaRDI QIDQ404529

Nikhil Padhye, Kalyanmoy Deb

Publication date: 4 September 2014

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1721.1/103318

zbMATH Keywords

genetic algorithmsparticle swarm optimizationalgorithmic linkingreal-parameter optimizationunified algorithms

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59)

Related Items (3)

Enhanced comprehensive learning particle swarm optimization ⋮ QUAntum particle swarm optimization: an auto-adaptive PSO for local and global optimization ⋮ LFM signal parameters estimation using optimization approach initialized by Lipschitz constant assisted DIRECT algorithm

Uses Software

• MOPSO

Cites Work

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• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• Improving differential evolution through a unified approach
• A review of particle swarm optimization. I: Background and development
• Parameter selection and adaptation in Unified Particle Swarm Optimization
• Particle Swarm Optimization
• A New Method of Constrained Optimization and a Comparison With Other Methods

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