Ghent University Academic Bibliography

Advanced

Constrained multi-objective antenna design optimization using surrogates

Prashant Singh, Marco Rossi, Ivo Couckuyt UGent, Dirk Deschrijver UGent, Hendrik Rogier UGent and Tom Dhaene UGent (2017) INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS. 30(6).
abstract
A novel surrogate-based constrained multi-objective optimization algorithm for simulation-driven optimization is proposed. The evolutionary algorithms usually applied in antenna design optimization typically require a large number of objective function evaluations to converge. The efficient constrained multiobjective optimization algorithm described in this paper identifies Pareto-optimal solutions satisfying the required constraints using very few function evaluations. This leads to substantial savings in time and drastically reduces the time to market for expensive antenna design optimization problems. The efficiency of the approach is demonstrated on the design of an L1-band GPS antenna. The algorithm automatically optimizes the antenna geometry, parametrized by 5 design variables with performance constraints on three objectives. The results are compared with well-established multiobjective optimization evolutionary algorithms.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
keyword
IBCN, antenna optimization, Bayesian optimization, multiobjective optimization, model-based optimization, surrogate-based optimization
journal title
INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS
volume
30
issue
6
article number
e2248
Web of Science type
Article
Web of Science id
000413161300022
ISSN
0894-3370
1099-1204
DOI
10.1002/jnm.2248
language
English
UGent publication?
yes
classification
A1
id
8537108
handle
http://hdl.handle.net/1854/LU-8537108
date created
2017-11-13 09:46:40
date last changed
2017-11-16 10:04:55
@article{8537108,
  abstract     = {A novel surrogate-based constrained multi-objective optimization algorithm for simulation-driven optimization is proposed. The evolutionary algorithms usually applied in antenna design optimization typically require a large number of objective function evaluations to converge. The efficient constrained multiobjective optimization algorithm described in this paper identifies Pareto-optimal solutions satisfying the required constraints using very few function evaluations. This leads to substantial savings in time and drastically reduces the time to market for expensive antenna design optimization problems. The efficiency of the approach is demonstrated on the design of an L1-band GPS antenna. The algorithm automatically optimizes the antenna geometry, parametrized by 5 design variables with performance constraints on three objectives. The results are compared with well-established multiobjective optimization evolutionary algorithms.},
  articleno    = {e2248},
  author       = {Singh, Prashant and Rossi, Marco and Couckuyt, Ivo and Deschrijver, Dirk and Rogier, Hendrik and Dhaene, Tom},
  issn         = {0894-3370},
  journal      = {INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS},
  keyword      = {IBCN,antenna optimization,Bayesian optimization,multiobjective optimization,model-based optimization,surrogate-based optimization},
  language     = {eng},
  number       = {6},
  title        = {Constrained multi-objective antenna design optimization using surrogates},
  url          = {http://dx.doi.org/10.1002/jnm.2248},
  volume       = {30},
  year         = {2017},
}

Chicago
Singh, Prashant, Marco Rossi, Ivo Couckuyt, Dirk Deschrijver, Hendrik Rogier, and Tom Dhaene. 2017. “Constrained Multi-objective Antenna Design Optimization Using Surrogates.” International Journal of Numerical Modelling-electronic Networks Devices and Fields 30 (6).
APA
Singh, Prashant, Rossi, M., Couckuyt, I., Deschrijver, D., Rogier, H., & Dhaene, T. (2017). Constrained multi-objective antenna design optimization using surrogates. INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS, 30(6).
Vancouver
1.
Singh P, Rossi M, Couckuyt I, Deschrijver D, Rogier H, Dhaene T. Constrained multi-objective antenna design optimization using surrogates. INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS. 2017;30(6).
MLA
Singh, Prashant, Marco Rossi, Ivo Couckuyt, et al. “Constrained Multi-objective Antenna Design Optimization Using Surrogates.” INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 30.6 (2017): n. pag. Print.