This study systematically optimized the geometric parameters of three typical cross-sections for curved-wall highway tunnel inner contours. Aiming to minimize the net excavation area, a unified genetic algorithm-based optimization framework was established for systematic comparison of four typical curved-wall section types and implemented on the Matlab(R2023b) platform, incorporating encoding, selection, crossover, and mutation operations for global optimization of geometric parameters across different section types. The optimized sections were further validated for structural performance using Midas GTS NX. Results show that the proposed multi-type optimization framework effectively reduced tunnel excavation areas across all section types, with mean optimization rates of 2.60% ± 0.21%, 2.11% ± 0.03%, 4.70% ± 0.02%, and 2.54% ± 0.02% (95% CI) achieved for single-circle, triple-circle Model-1, triple-circle Model-2, and five-circle sections, respectively, providing quantitative evidence for section-type selection in highway tunnel design. In terms of structural performance, the optimized sections demonstrated favorable axial force and bending moment characteristics. The findings provide a quantitative basis combining economic efficiency and structural rationality for tunnel section design, offering significant engineering application value and technical support for standardized and refined highway tunnel design in China.
Zhu et al. (Mon,) studied this question.