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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Vydané v:	2023 5th International Conference on Data-driven Optimization of Complex Systems (DOCS) s. 1 - 7
Hlavní autori:	Wang, Xilu, Jin, Yaochu
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 22.09.2023
Predmet:	acquisition function Bayes methods Bayesian optimization Benchmark testing Closed box Complex systems expected improvement expensive multi-objective optimization Mathematical models Optimization Pareto optimization
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