An Improved Interval Evidential Reasoning Method for Freight Railway Route Selection Decision-Making in Mining Areas

In the decision-making process for railway route selection in mining areas, it not only impacts engineering construction and operational costs but also influences regional economic development and ecological conservation. To better handle uncertain information in decision-making and minimize the effects of human bias, this study proposes an improved interval evidential reasoning method. First, a bottom-up approach is used to construct a decision-making index system. The weights of the criteria, derived from three objective weighting methods—Entropy Method, Standard Deviation Method, and Criteria Importance Through Intercriteria Correlation Method—are treated as evidence. These weights are then fused using evidential reasoning to determine the final criteria weights. Next, the evaluation values of each alternative are transformed into relative importance scores. By introducing interval probability density functions, these scores are further converted into belief degrees. Finally, the interval evidential reasoning algorithm is applied to rank the alternatives. Comparative analysis with existing decision-making methods demonstrates that the proposed approach reduces unnecessary human intervention, effectively handles and preserves uncertainties in evaluation data, and produces results with higher credibility and interpretability.