Hemker, T. ; Glocker, M. ; Gersem, Herbert De ; Stryk, Oskar von ; Weiland, Thomas (2006):
Mixed-integer simulation-based optimization for a superconductive magnet design.
pp. 125-127, Achen, Sixth International Conference on Computational Elektromagnetics, Proceedings, 4-6 April 2006 in Aachen, Achen, [Conference or Workshop Item]
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Abstract
The optimization of continuous parameters in electrotechnical designs using electromagnetic field simulation is already standard. Typically, the simulation tools only carry out evaluations of the objective function and do not provide gradient information. If in addition to continuous design parameters also integer design parameters have to be optimized, only computational expensive random search methods like genetic algorithms are well known. In this paper, we present a new sequential modeling approach to solve mixed-integer simulation-based optimiza-tion problems for an electrotechnical design problem for superconductive magnets. Each step of this approach uses stochastic modeling techniques to predict the simulation output by a surrogate function. The surrogate function treats the integer variables as real-valued ones. New promising parameter con-figurations are predicted by a “branch-and-bound” method, which solves the purely continuous subproblems by classical optimization methods for continuous and differentiable functions. The additional information of these simulation runs improves the quality of the surrogate function step by step. The proposed approach is applied to optimize the distribution of coil blocks and coil windings of a superconduc-tive magnet such that a maximal homogeneity of the magnetic field in the aperture is achieved.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2006 |
| Creators: | Hemker, T. ; Glocker, M. ; Gersem, Herbert De ; Stryk, Oskar von ; Weiland, Thomas |
| Title: | Mixed-integer simulation-based optimization for a superconductive magnet design |
| Language: | English |
| Abstract: | The optimization of continuous parameters in electrotechnical designs using electromagnetic field simulation is already standard. Typically, the simulation tools only carry out evaluations of the objective function and do not provide gradient information. If in addition to continuous design parameters also integer design parameters have to be optimized, only computational expensive random search methods like genetic algorithms are well known. In this paper, we present a new sequential modeling approach to solve mixed-integer simulation-based optimiza-tion problems for an electrotechnical design problem for superconductive magnets. Each step of this approach uses stochastic modeling techniques to predict the simulation output by a surrogate function. The surrogate function treats the integer variables as real-valued ones. New promising parameter con-figurations are predicted by a “branch-and-bound” method, which solves the purely continuous subproblems by classical optimization methods for continuous and differentiable functions. The additional information of these simulation runs improves the quality of the surrogate function step by step. The proposed approach is applied to optimize the distribution of coil blocks and coil windings of a superconduc-tive magnet such that a maximal homogeneity of the magnetic field in the aperture is achieved. |
| Place of Publication: | Achen |
| Divisions: | 18 Department of Electrical Engineering and Information Technology 18 Department of Electrical Engineering and Information Technology > Institute for Accelerator Science and Electromagnetic Fields > Electromagnetic Field Theory (until 31.12.2018 Computational Electromagnetics Laboratory) 18 Department of Electrical Engineering and Information Technology > Institute for Accelerator Science and Electromagnetic Fields 20 Department of Computer Science 20 Department of Computer Science > Simulation, Systems Optimization and Robotics Group |
| Event Title: | Sixth International Conference on Computational Elektromagnetics, Proceedings, 4-6 April 2006 in Aachen |
| Event Location: | Achen |
| Date Deposited: | 09 Jul 2019 09:55 |
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