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Scalability of surrogate-assisted multi-objective optimization of antenna structures exploiting variable-fidelity electromagnetic simulation models

Abstract

Multi-objective optimization of antenna structures is a challenging task due to high-computational cost of evaluating the design objectives as well as large number of adjustable parameters. Design speedup can be achieved by means of surrogate-based optimization techniques. In particular, a combination of variable-fidelity electromagnetic (EM) simulations, design space reduction techniques, response surface approximation (RSA) models, and design refinement methods, permits identification of the Pareto-optimal set of designs within reasonable timeframe. Here, a study concerning scalability of surrogate-assisted multi-objective antenna design is carried out based on a set of benchmark problems with the dimensionality of the design space ranging from six to 24 and a CPU cost of the EM antenna model from 10 to 20 minutes per simulation. Numerical results indicate that the computational overhead of the design process increases more or less quadratically with the number of adjustable geometry parameters of the antenna structure at hand, which is a promising result from the point of view of handling even more complex problems.

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Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
ENGINEERING OPTIMIZATION no. 48, edition 10, pages 1778 - 1792,
ISSN: 0305-215X
Language:
English
Publication year:
2016
Bibliographic description:
Kozieł S., Bekasiewicz A.: Scalability of surrogate-assisted multi-objective optimization of antenna structures exploiting variable-fidelity electromagnetic simulation models// ENGINEERING OPTIMIZATION. -Vol. 48, iss. 10 (2016), s.1778-1792
DOI:
Digital Object Identifier (open in new tab) 10.1080/0305215x.2015.1137565
Verified by:
Gdańsk University of Technology

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