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Low-Cost Multi-Objective Optimization of Antennas By Means Of Generalized Pareto Ranking Bisection Algorithm

This paper introduces a generalized Pareto ranking bisection algorithm for low-cost multi-objective design optimization of antenna structures. The algorithm allows for identifying a set of Pareto optimal sets of parameters (that represent the best trade-offs between considered objectives) by iterative partitioning of the intervals connecting previously found designs and executing a Pareto-ranking-based poll search. The initial approximation of the Pareto front found using the bisection procedure is subsequently refined to the level of the high-fidelity EM model of the antenna at hand using local optimization. A serious limitation of the original bisection algorithm was that only two objectives could be considered. The generalized version proposed here allows for handling any number of design goals. An improved poll search procedure has also been developed and incorporated. Our algorithm has been demonstrated using an example of a UWB monopole antenna with three figures of interest taken into account: structure size, reflection response, and gain variability.

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DOI
Digital Object Identifier link open in new tab 10.1049/cp.2018.1089
Category
Aktywność konferencyjna
Type
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Language
angielski
Publication year
2018

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