A New Expected Improvement Acquisition Function for Expensive Multi-Objective Optimization

While Bayesian optimization, a popular solution to black-box optimization problems, has been extended to handle expensive multi-objective optimization problems (MOPs), expected improvement (EI), a commonly used acquisition function, for MOPs is often either computationally expensive or inefficient t...

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Bibliographic Details

Published in:	2023 5th International Conference on Data-driven Optimization of Complex Systems (DOCS) pp. 1 - 7
Main Authors:	Wang, Xilu, Jin, Yaochu
Format:	Conference Proceeding
Language:	English
Published:	IEEE 22.09.2023
Subjects:	acquisition function Bayes methods Bayesian optimization Benchmark testing Closed box Complex systems expected improvement expensive multi-objective optimization Mathematical models Optimization Pareto optimization
Online Access:	Get full text
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