An Expensive Multi-Objective Evolutionary Algorithm with RBF-IDW Surrogate Model

In surrogate-assisted multi-objective evolutionary optimization, surrogate models provide approximations for each solution on each objective, with varying quality. In the proposed algorithm, the RBF-IDW surrogate model replaces the Gaussian process model used in the original algorithm, constructing...

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Veröffentlicht in:	2024 International Conference on New Trends in Computational Intelligence (NTCI) S. 86 - 90
Hauptverfasser:	Liu, Yuhao, Fang, Hongyi, Li, Fei
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 18.10.2024
Schlagworte:	Adaptation models Approximation algorithms Computational modeling Gaussian processes infill criterion Linear programming multi-/many objective optimization Optimization performance indicator Prediction algorithms Predictive models Surrogate model Uncertainty
Online-Zugang:	Volltext
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