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Two-level genetic algorithm for optimization of a die press

Peter Sergeant (UGent) , Guillaume Crevecoeur (UGent) and Luc Dupré (UGent)
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Abstract
For many electromagnetic applications, it is possible to develop both a fast but inaccurate model (coarse model) and a slow but accurate model (fine model). Space mapping techniques are able to optimize the fine model by taking advantage of the coarse model. Convergence however is not guaranteed. The two level genetic algorithm has the advantages of a conventional genetic algorithm (robustness, global convergence), but it is faster as it benefits from information in the inaccurate model. The two level genetic algorithm is applied to the die-press bench mark test case (TEAM workshop problem 25).
Keywords
genetic algorithm, optimization, space mapping

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MLA
Sergeant, Peter, Guillaume Crevecoeur, and Luc Dupré. “Two-level Genetic Algorithm for Optimization of a Die Press.” Workshop on Optimization and Inverse Problems in Electromagnetism, 10th, Proceedings. Ed. Hartmut Brauer & Jens Haueisen. 98693 Ilmenau, Germany: Technische Universität Ilmenau, 2008. 4–5. Print.
APA
Sergeant, Peter, Crevecoeur, G., & Dupré, L. (2008). Two-level genetic algorithm for optimization of a die press. In H. Brauer & J. Haueisen (Eds.), Workshop on Optimization and Inverse Problems in Electromagnetism, 10th, Proceedings (pp. 4–5). Presented at the 10th Workshop on Optimization and Inverse Problems in Electromagnetism, 98693 Ilmenau, Germany: Technische Universität Ilmenau.
Chicago author-date
Sergeant, Peter, Guillaume Crevecoeur, and Luc Dupré. 2008. “Two-level Genetic Algorithm for Optimization of a Die Press.” In Workshop on Optimization and Inverse Problems in Electromagnetism, 10th, Proceedings, ed. Hartmut Brauer and Jens Haueisen, 4–5. 98693 Ilmenau, Germany: Technische Universität Ilmenau.
Chicago author-date (all authors)
Sergeant, Peter, Guillaume Crevecoeur, and Luc Dupré. 2008. “Two-level Genetic Algorithm for Optimization of a Die Press.” In Workshop on Optimization and Inverse Problems in Electromagnetism, 10th, Proceedings, ed. Hartmut Brauer and Jens Haueisen, 4–5. 98693 Ilmenau, Germany: Technische Universität Ilmenau.
Vancouver
1.
Sergeant P, Crevecoeur G, Dupré L. Two-level genetic algorithm for optimization of a die press. In: Brauer H, Haueisen J, editors. Workshop on Optimization and Inverse Problems in Electromagnetism, 10th, Proceedings. 98693 Ilmenau, Germany: Technische Universität Ilmenau; 2008. p. 4–5.
IEEE
[1]
P. Sergeant, G. Crevecoeur, and L. Dupré, “Two-level genetic algorithm for optimization of a die press,” in Workshop on Optimization and Inverse Problems in Electromagnetism, 10th, Proceedings, Ilmenau, Germany, 2008, pp. 4–5.
@inproceedings{523347,
  abstract     = {For many electromagnetic applications, it is possible to develop both a fast but inaccurate model (coarse model) and a slow but accurate model (fine model). Space mapping techniques are able to optimize the fine model by taking advantage of the coarse model. Convergence however is not guaranteed. The two level genetic algorithm has the advantages of a conventional genetic algorithm (robustness,
global convergence), but it is faster as it benefits from information in the inaccurate model. The two level genetic algorithm is applied to the die-press bench mark test case (TEAM workshop problem 25).},
  author       = {Sergeant, Peter and Crevecoeur, Guillaume and Dupré, Luc},
  booktitle    = {Workshop on Optimization and Inverse Problems in Electromagnetism, 10th, Proceedings},
  editor       = {Brauer, Hartmut and Haueisen, Jens},
  keywords     = {genetic algorithm,optimization,space mapping},
  language     = {eng},
  location     = {Ilmenau, Germany},
  pages        = {4--5},
  publisher    = {Technische Universität Ilmenau},
  title        = {Two-level genetic algorithm for optimization of a die press},
  year         = {2008},
}