A Kriging model-based expensive multiobjective optimization algorithm using R2 indicator of expectation improvement

DOI10.1155/2020/9474580zbMath1459.90193OpenAlexW3037177522MaRDI QIDQ779579

Ding Han, Jianrong Zheng

Publication date: 13 July 2020

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

Full work available at URL: https://doi.org/10.1155/2020/9474580

Mathematics Subject Classification ID

Optimal statistical designs (62K05) Multi-objective and goal programming (90C29) Nonlinear programming (90C30)

Uses Software

• MOEA/D
• SPEA2
• EGO
• ParEGO
• MOPSO
• HypE
• MOMBI

Cites Work

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• ParEGO extensions for multi-objective optimization of expensive evaluation functions
• On the design of optimization strategies based on global response surface approximation models
• Kriging metamodeling in simulation: a review
• Efficient global optimization of expensive black-box functions
• Optimal Latin-hypercube designs for computer experiments
• Expected improvement based infill sampling for global robust optimization of constrained problems
• Multiobjective optimization of expensive-to-evaluate deterministic computer simulator models
• A taxonomy of global optimization methods based on response surfaces
• Evolutionary Multi-Criterion Optimization

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