Improving High-dimensional Simulation-driven Optimization

Research output: Contribution to journalArticle

Abstract

Computer simulations are being extensively used as a partial substitute for real-world experiments. Such simulations are often computationally intensive and hence metamodels are used to approximate them and to yield estimated output values more economically. While this setup can work well in low dimensional problems it can struggle in high-dimensional ones due to poor metamodel prediction accuracy. As such this study examines the application of dimensionality-reduction procedures during the search so that a simplified problems is formulated which is easier to solve and which could yield a better solution of the original one. An extensive performance analysis with both mathematical test functions and an engineering application shows the effectiveness of the proposed approach.
Original languageEnglish
Pages (from-to)23-31
Number of pages9
JournalWSEAS Transactions on Information Science and Applications
Volume17
DOIs
StatePublished - 2020

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