The construction of expressways in rugged mountainous areas faces multiple challenges, including complex terrain, variable geological conditions, fragile ecological environment, and high safety risks during construction and operation. Route scheme optimization is a key step in the design phase. To address the technical difficulties in determining the weight of indicators, quantifying qualitative indicators, and conducting multi-attribute comprehensive evaluation in the selection of mountainous highway schemes, a route scheme optimization method for rugged mountainous expressways based on cloud model and TOPSIS is studied. By analyzing the main factors affecting the route selection of mountainous expressways, 16 indicators are selected from four aspects: route design, unfavorable geology, safety performance, and environmental impact to establish an evaluation index system. Then, a qualitative indicator quantification method based on the cloud model is designed. The subjective and objective weights calculated by the analytic hierarchy process and entropy weight method are integrated using the product method to obtain the comprehensive weight of indicators. Finally, a route scheme optimization model for rugged mountainous highways is constructed based on TOPSIS, which achieves scheme ranking by calculating the relative closeness of alternative schemes to the ideal scheme. Taking the route selection of the Xihe-Dangchang Expressway in Gansu Province as an example, the model in this paper is verified and analyzed. The research results show that the cloud model has significant effects in qualitative indicator quantification, effectively balancing the randomness and ambiguity of evaluation semantics. The comprehensive weight is more objective and reasonable, and the weight ranking highly aligns with the actual situation on site. The route scheme optimization based on TOPSIS achieves precise differentiation between good and bad schemes, and the optimization results have good consistency with the actual engineering situation. The research findings can provide quantitative support for the early decision-making of route schemes for rugged mountainous expressways, effectively reducing the risks of later engineering changes and safety issues caused by improper route selection.