Gradient-Enhanced NSGA-II Algorithm Complex Permittivity Extraction of Polymer Materials Using

2026-07-11

AI Summary

This study addresses the challenges of local optima and non-unique solutions in extracting the complex permittivity of polymers by proposing a gradient-enhanced non-dominated sorting genetic algorithm (G-NSGA-II). For the first time, gradient information is incorporated into the NSGA-II framework, combined with transmission and reflection coefficients from multi-thickness samples to formulate a multidimensional constrained model. A population stagnation detection mechanism is further introduced to adaptively trigger local refinement. Experimental validation on six representative polymers in the 20–40 GHz band demonstrates that the proposed method significantly accelerates convergence—reducing the required generations by approximately 50%—and enhances inversion robustness. The retrieved complex permittivity and thickness values show excellent agreement with literature data and direct measurements, thereby substantially improving the efficiency and reliability of broadband dielectric characterization.

Abstract

This paper presents gradient-enhanced non-dominated sorting genetic algorithm II (G-NSGA-II) to address the challenges of local optima and solution non-uniqueness in the complex permittivity extraction problem for the first time. This adaptive hybrid algorithm integrates the global exploration capability of NSGA-II with gradient-based local refinement, triggered by a population-stagnation detection mechanism. Furthermore, multi-dimensional constraints are incorporated by jointly optimizing transmission and reflection coefficients across multiple sample thicknesses. Experimental validation conducted on six typical polymers in the 20--40 GHz band demonstrates that the retrieved relative permittivity and thicknesses are in high agreement with literature values and physical measurements. Compared to standard heuristic and gradient-based algorithms, the proposed G-NSGA-II reduces the number of generations required for convergence by approximately 50\%. This significant improvement in speed, combined with enhanced robustness, provides a highly reliable and efficient solution for broadband dielectric characterization in architectural and electromagnetic engineering. The simple measurement method and the proposed efficient algorithm allow for a rapid evalutaion of wireless performance within indoor environments. This approach serves as a valuable tool for optimizing existing wireless layouts and improving network performance.

Problem

• complex permittivity extraction
• local optima
• solution non-uniqueness
• polymer materials
• broadband dielectric characterization

Innovation

• gradient-enhanced NSGA-II
• complex permittivity extraction
• multi-thickness optimization
• population-stagnation detection
• broadband dielectric characterization