Repozytorium publikacji - Politechnika Gdańska

Multi-objective optimization (MO) allows for obtaining comprehensive information about possible design trade-offs of a given antenna structure. Yet, executing MO using the most popular class of techniques, population-based metaheuristics, may be computationally prohibitive when full-wave EM analysis is utilized for antenna evaluation. In this work, a low-cost and fully deterministic MO methodology is introduced. The proposed generalized Pareto ranking bisection algorithm permits identifying a set of Pareto optimal sets of parameters representing the best trade-offs between considered objectives. The subsequent designs are found by iterative partitioning of the intervals connecting previously obtained designs and executing 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. The proposed framework overcomes a serious limitation of the original, recently reported, bisection algorithm, which was only capable of considering two objectives. 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 two examples of UWB monopole antennas with four figures of interest taken into account: structure size, reflection response, total efficiency, and gain variability.

Autorzy

• Sigmar Unnsteinsson,
• prof. dr inż. Sławomir Kozieł link otwiera się w nowej karcie