Mountain railway alignment optimization based on landform recognition and presetting of dominating structures

Abstract

Abstract Mountain railway alignment optimization has always been a challenge for designers and researchers in this field. It is extremely difficult for existing methods that optimize alignments before major structures to generate a better alignment than the best one provided by human designers when the terrain is drastically undulating between the start and endpoints. To fill this gap, a “structures before alignments” design process is proposed in this paper. Primarily, a landform recognition method is devised for recognizing dominating landforms. Then, a bi?level alignment optimization model is proposed, with the upper level dedicated to characterizing dominating structures and the lower level focusing on optimizing the entire alignments. To solve this bi?level model, a three?stage optimization method is designed. At the first stage, a scanning process and screening operators are devised for generating all the possible locations of dominating structures. At the second stage, a hierarchical multi?criteria decision?making procedure is applied for selecting the optimized dominating structure layouts. At the third stage, alignments are optimized based on the determined structure layouts using a bi?objective optimization method, which minimizes construction cost and geo?hazard risk simultaneously. The proposed model and solution method are applied to two real?world cases whose results verify their capabilities in producing alignment alternatives with better combinations of construction cost and geo?hazard risk than manually designed alternatives.