A framework for constrained optimization problems based on a modified particle swarm optimization

DOI10.1155/2016/8627083zbMath1400.90280OpenAlexW2503621173WikidataQ59140963 ScholiaQ59140963MaRDI QIDQ1793699

Jianjun Luo, Zhanxia Zhu, Biwei Tang

Publication date: 12 October 2018

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2016/8627083

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Approximation methods and heuristics in mathematical programming (90C59)

Cites Work

• An improved self-adaptive PSO algorithm with detection function for multimodal function optimization problems
• A rank based particle swarm optimization algorithm with dynamic adaptation
• Stochastic convergence analysis and parameter selection of the standard particle swarm optimization algorithm
• An effective co-evolutionary differential evolution for constrained optimization
• A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization
• The particle swarm optimization algorithm: Convergence analysis and parameter selection
• A Convergence Proof for the Particle Swarm Optimiser
• Minimization by Random Search Techniques

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