An efficient multi-objective PSO algorithm assisted by Kriging metamodel for expensive black-box problems

DOI10.1007/s10898-016-0428-2zbMath1359.90130OpenAlexW2336895434MaRDI QIDQ506477

Jianjun Zhao, Haoxiang Jie, Liangliang, Jianwan Ding, Yi-Zhong Wu

Publication date: 1 February 2017

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

Full work available at URL: https://doi.org/10.1007/s10898-016-0428-2

zbMATH Keywords

multi-objective optimizationparticle swarm optimizationblack-box functionkriging metamodel

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Approximation methods and heuristics in mathematical programming (90C59)

Uses Software

• DACE
• EGO
• MOPSO

Cites Work

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• Multivariate adaptive regression splines
• Efficient global optimization of expensive black-box functions
• Design and analysis of computer experiments. With comments and a rejoinder by the authors
• Response surface approximation of Pareto optimal front in multi-objective optimization
• Efficient Pareto frontier exploration using surrogate approximations

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