A multi-start opposition-based particle swarm optimization algorithm with adaptive velocity for bound constrained global optimization

DOI10.1007/s10898-012-9913-4zbMath1263.90065OpenAlexW2019884884MaRDI QIDQ1937953

Massimiliano Kaucic

Publication date: 1 February 2013

Published in: Journal of Global Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10898-012-9913-4

zbMATH Keywords

hybrid methodsparticle swarm optimizationbound constrained optimizationopposition-based computingrestart techniques

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Approximation methods and heuristics in mathematical programming (90C59)

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Uses Software

• PSwarm
• SPOT

Cites Work

• A numerical evaluation of several stochastic algorithms on selected continuous global optimization test problems
• Self-adaptive velocity particle swarm optimization for solving constrained optimization problems
• The particle swarm optimization algorithm: Convergence analysis and parameter selection
• A dynamic inertia weight particle swarm optimization algorithm
• A particle swarm pattern search method for bound constrained global optimization
• Experimental research in evolutionary computation. The new experimentalism
• A novel population initialization method for accelerating evolutionary algorithms
• Blowing up of non-commutative smooth surfaces
• Constrained optimization with an improved particle swarm optimization algorithm
• Clan particle swarm optimization
• Opposition-Based Computing
• Evolutionary Multi-Criterion Optimization

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