Mixed-Integer Nonlinear Design Optimization of a Superconductive Magnet With Surrogate Functions

The numerical optimization of continuous parameters in electrotechnical design using electromagnetic field simulation is already standard. When integer-valued variables are involved, the complexity of the optimization problem rises drastically. In this paper, we describe a new sequential surrogate o...

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Bibliographic Details
Published in:IEEE transactions on magnetics 2008-06, Vol.44 (6), p.1110-1113
Main Authors: Hemker, T., De Gersem, H., von Stryk, O., Weiland, T.
Format: Article
Language:English
Subjects:
Computational modeling
Computer simulation
Cross-disciplinary physics: materials science
rheology
Design optimization
Electromagnetic fields
Exact sciences and technology
Magnetic separation
Magnetism
Magnetostatics
Materials science
Mathematical analysis
Mathematical models
mixed-integer nonlinear optimization
Nonlinear programming
Numerical simulation
Optimization
Optimization methods
Other topics in materials science
Physics
simulation-based optimization
Superconducting coils
Superconducting magnets
Superconductivity
Superconductors
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Summary:The numerical optimization of continuous parameters in electrotechnical design using electromagnetic field simulation is already standard. When integer-valued variables are involved, the complexity of the optimization problem rises drastically. In this paper, we describe a new sequential surrogate optimization approach for simulation-based mixed-integer nonlinear programming (NLP) problems. We apply the method for the optimization of combined integer- and real-valued geometrical parameters of the coils of a superconductive magnet.
ISSN:0018-9464
1941-0069
DOI:10.1109/TMAG.2007.916165