充气膜结构的交叉索网布置方式对其整体受力及经济性有显著影响，合理的交叉索网布置是提升结构综合性能的关键。结合实际工程需求，设计既满足结构性能又兼顾低碳经济的索网布置，是一个复杂的多目标优化问题。本研究针对此问题，研究了几何尺寸、物理参数及索网布置对结构变形、索膜内力及碳排放的影响，并构建了多目标优化函数。基于神经网络模型，在最小化多目标函数的前提下，求解出最优索网布置方式。有限元模型验证结果显示，该多目标优化神经网络模型所求解的索网布置方式能够使充气膜结构具备良好的力学性能和经济性，钢材用量比传统方法有效降低6.9%。本研究为充气膜结构交叉索网布置提供了高效、低碳的优化方案，具有重要工程应用价值。

The layout of cable-net in air-supported membrane structures significantly affects the overall mechanical performance and economic efficiency. An optimal cable-net layout is crucial for enhancing the comprehensive performance of air-supported membrane structures. Combining the practical engineering requirements, designing a cable-net layout that satisfies both structural performance and low-carbon economy is a complex multi-objective optimization problem. Aiming at this problem, this study investigates the influences of geometric dimensions, physical parameters, and cable net layout on the structural deformation, internal forces of cables and membranes, and carbon emissions, and establishes a multi-objective optimization function. Based on a neural network model, the optimal cable-net layout is derived under the condition of minimizing the multi-objective function. Finite element model validation demonstrates that the cable-net layout obtained by the proposed multi-objective optimization neural network model ensures excellent mechanical performance and economic efficiency for air-supported membrane structures. This study provides a efficient and low-carbon optimization solution for cable-net layout in air-supported membrane structures, providing practical significance for engineering applications.