Pareto Ranking Bisection Algorithm for EM-Driven Multi-Objective Design of Antennas in Highly-Dimensional Parameter Spaces - Publikacja - MOST Wiedzy

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Pareto Ranking Bisection Algorithm for EM-Driven Multi-Objective Design of Antennas in Highly-Dimensional Parameter Spaces

Abstrakt

A deterministic technique for fast surrogate-assisted multi-objective design optimization of antennas in highly-dimensional parameters spaces has been discussed. In this two-stage approach, the initial approximation of the Pareto set representing the best compromise between conflicting objectives is obtained using a bisection algorithm which finds new Pareto-optimal designs by dividing the line segments interconnecting previously found optimal points, and executing poll-type search that involves Pareto ranking. The initial Pareto front is generated at the level of the coarsely-discretized EM model of the antenna. In the second stage of the algorithm, the high-fidelity Pareto designs are obtained through optimization of corrected local-approximation models. The considered optimization method is verified using a 17-variable uniplanar antenna operating in ultra-wideband frequency range. The method is compared to three state-of-the-art surrogate-assisted multi-objective optimization algorithms.

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Informacje szczegółowe

Kategoria:
Aktywność konferencyjna
Typ:
materiały konferencyjne indeksowane w Web of Science
Opublikowano w:
Procedia Computer Science nr 108, strony 1453 - 1462,
ISSN: 1877-0509
Tytuł wydania:
International Conference on Computational Science (ICCS) strony 1453 - 1462
Język:
angielski
Rok wydania:
2017
Opis bibliograficzny:
Bekasiewicz A., Kozieł S., Leifsson L., Du X..: Pareto Ranking Bisection Algorithm for EM-Driven Multi-Objective Design of Antennas in Highly-Dimensional Parameter Spaces, W: International Conference on Computational Science (ICCS), 2017, ,.
DOI:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1016/j.procs.2017.05.102
Weryfikacja:
Politechnika Gdańska

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