NDLI: Multiobjective global surrogate modeling, dealing with the 5-percent problem

Content Provider	Springer Nature Link
Author	Gorissen, Dirk Couckuyt, Ivo Laermans, Eric Dhaene, Tom
Copyright Year	2009
Abstract	When dealing with computationally expensive simulation codes or process measurement data, surrogate modeling methods are firmly established as facilitators for design space exploration, sensitivity analysis, visualization, prototyping and optimization. Typically the model parameter (=hyperparameter) optimization problem as part of global surrogate modeling is formulated in a single objective way. Models are generated according to a single objective (accuracy). However, this requires an engineer to determine a single accuracy target and measure upfront, which is hard to do if the behavior of the response is unknown. Likewise, the different outputs of a multi-output system are typically modeled separately by independent models. Again, a multiobjective approach would benefit the domain expert by giving information about output correlation and enabling automatic model type selection for each output dynamically. With this paper the authors attempt to increase awareness of the subtleties involved and discuss a number of solutions and applications. In particular, we present a multiobjective framework for global surrogate model generation to help tackle both problems and that is applicable in both the static and sequential design (adaptive sampling) case.
Starting Page	81
Ending Page	98
Page Count	18
File Format	PDF
ISSN	01770667
Journal	Engineering with Computers
Volume Number	26
Issue Number	1
e-ISSN	14355663
Language	English
Publisher	Springer-Verlag
Publisher Date	2009-08-07
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Surrogate modeling Metamodeling Error estimation Performance measures Model selection Multiobjective optimization Adaptive sampling Hyperparameter optimization ApplicationMathematics/Computational Methods of Engineering Mechanics Calculus of Variations and Optimal Control; Optimization Systems Theory, Control Math. Applications in Chemistry Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Engineering Computer Science Applications Modeling and Simulation Software

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