Open AccessMulti-Objective Design Optimization of Planar Yagi-Uda Antenna Using Physics-Based Surrogates and Rotational Design Space Reduction
Author(s) -
Sławomir Kozieł,
Adrian Bekasiewicz,
Leifur Leifsson
Publication year - 2015
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2015.05.219
Subject(s) - computer science , antenna (radio) , reduction (mathematics) , planar , mathematical optimization , surrogate model , discretization , multi objective optimization , space (punctuation) , evolutionary algorithm , set (abstract data type) , pareto principle , dimensionality reduction , space mapping , algorithm , mathematics , telecommunications , geometry , artificial intelligence , mathematical analysis , computer graphics (images) , programming language , operating system
A procedure for low-cost multi-objective design optimization of antenna structures is discussed. The major stages of the optimization process include: (i) an initial reduction of the search space aimed at identifying its relevant subset containing the Pareto-optimal design space, (ii) construction—using sampled coarse-discretization electromagnetic (EM) simulation data—of the response surface approximation surrogate, (iii) surrogate optimization using a multi-objective evolutionary algorithm, and (iv) the Pareto front refinement. Our optimization procedure is demonstrated through the design of a planar quasi Yagi-Uda antenna. The final set of designs representing the best available trade-offs between conflicting objectives is obtained at a computational cost corresponding to about 172 evaluations of the high-fidelity EM antenna model
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