Parallel multi-objective Bayesian optimization approaches based on multi-fidelity surrogate modeling

Quan Lin; Jiexiang Hu; Qi Zhou

doi:10.1016/j.ast.2023.108725

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Parallel multi-objective Bayesian optimization approaches based on multi-fidelity surrogate modeling

Quan Lin Jiexiang Hu Qi Zhou

Year: 2023 Journal: Aerospace Science and Technology Vol: 143 Pages: 108725-108725 Publisher: Elsevier BV

DOI: 10.1016/j.ast.2023.108725

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Keywords:

Surrogate model Computer science Benchmark (surveying) Mathematical optimization Fidelity Bayesian optimization Optimization problem Convergence (economics) Algorithm Machine learning Mathematics

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Advanced Multi-Objective Optimization Algorithms

Physical Sciences → Computer Science → Computational Theory and Mathematics

Optimal Experimental Design Methods

Social Sciences → Decision Sciences → Management Science and Operations Research

Probabilistic and Robust Engineering Design

Social Sciences → Decision Sciences → Statistics, Probability and Uncertainty

Parallel multi-objective Bayesian optimization approaches based on multi-fidelity surrogate modeling

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