Multi-objective optimization based on meta-modeling by using support vector regression

DOI10.1007/s11081-008-9063-1zbMath1171.65051OpenAlexW2035332798MaRDI QIDQ833457

Hirotaka Nakayama, Min Su Yoon, Ye Boon Yun

Publication date: 12 August 2009

Published in: Optimization and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11081-008-9063-1

zbMATH Keywords

multi-objective optimizationnumerical examplesPareto frontierevolutionary multi-objective optimizationsupport vector regressionsequential approximation method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Multi-objective and goal programming (90C29)

Related Items (2)

Considering dynamic Pareto frontiers in decision making ⋮ Multi-fidelity deep neural network surrogate model for aerodynamic shape optimization

Uses Software

• SPEA2
• EGO

Cites Work

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• Multiple criteria decision making with generalized DEA and an aspiration level method
• Theory of multiobjective optimization
• Efficient global optimization of expensive black-box functions
• Simulation-based optimization using computational intelligence
• Support-vector networks
• Generation of efficient frontiers in multi-objective optimization problems by generalized data envelopment analysis.

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