# Research on the optimal selection method for railway line routes in complex and challenging mountainous areas taking into account ecological protection

## TL;DR

This paper introduces a new method for selecting railway routes in mountainous areas that balances environmental protection with engineering efficiency.

## Contribution

A novel decision-making framework integrating ecological and engineering factors using fuzzy numbers and multi-attribute utility theory.

## Key findings

- The model validated full-tunnel passage through sensitive zones as optimal with a relative closeness of 0.5202.
- The methodology reduces environmental impact while maintaining cost efficiency and safety.
- Combination weighting using G2 and CRITIC methods improved the reliability of indicator weights.

## Abstract

This study addresses the coordinated optimization of ecological conservation and engineering efficiency in railway route planning through challenging mountainous terrain, proposing a selection methodology that prioritizes environmental protection. A comprehensive evaluation system with 20 indicators was developed across technique, economy, environment, and social dimensions. Key considerations include impacts on ecologically sensitive zones, engineering risks, and low-carbon development objectives. The weighting system integrates expert knowledge (G2 method) and data patterns (CRITIC method), optimized through relative entropy to balance subjective and objective information, enhancing weighting reliability. A decision-making model was established using trapezoidal fuzzy numbers for qualitative indicators and multi-attribute utility theory. Projection values and comprehensive relative closeness calculations enable quantitative scheme evaluation. Applied to a high-speed railway crossing protected areas, the model validated Scheme II (full-tunnel passage through sensitive zones) as optimal (0.5202 relative closeness), demonstrating cost efficiency, minimal environmental impact, and enhanced safety – consistent with practical engineering outcomes. The methodology provides a scientifically grounded decision-making framework balancing ecological preservation and engineering viability, supporting green transportation transformation under carbon neutrality goals. Combination weighting.