Parameter Optimization of Functional Textile Materials for Building Sunshade Based on Multi-Objective Genetic Algorithm

Lei Guo

Article
2026 / Volume 9 / Pages 807-827
Received 29 July 2025; Accepted 25 August 2025; Published 31 March 2026
https://doi.org/10.31881/TLR.2026.807

Abstract
Existing functional textile materials for building shading lack effective methods for parameter coordination and optimization across multiple performance objectives, making it difficult to simultaneously meet comprehensive requirements for shading, light transmission, and energy savings. To address this issue, this paper proposes a pa-rameter optimization framework based on a multi-objective genetic algorithm (MOGA). It constructs a perfor-mance model with fabric density, coating thickness, and fiber thermal conductivity as variables, and shading effi-ciency, visible light transmittance, and thermal resistance as objective functions. MOGA is employed to optimize these parameters and obtain an optimal solution set that achieves coordinated multi-performance. Experimental results show that changes in coating thickness and thermal conductivity significantly affect visible light transmit-tance and thermal resistance, verifying the effectiveness of the multi-objective genetic algorithm for optimizing building shading materials. This has important engineering application value.

Keywords
multi-objective genetic algorithm, functional textile materials, performance evaluation model, visible light trans-mittance, thermal resistance