A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Mountain Railway Alignment Optimization with Bidirectional Distance Transform and Genetic Algorithm
Various challenging constraints must be satisfied in railway alignment design for topographically complex mountainous regions. The alignment design for such environments is so challenging that existing methodologies have great difficulties in automatically generating viable railway alignment alternatives. We solve this problem with a hybrid method in which a bidirectional distance transform (DT) algorithm automatically selects control points before a genetic algorithm (GA) refines the alignment. This approach solves the problems of (1) determining the appropriate distribution of control points in the GA and (2) producing alignments that deviate significantly from the DT‐optimized paths. Automatic design of backtracking curves and dynamic generation of vertical points of intersection handling multiple constraints are developed to improve the GA performance. This method has been applied to a real case on the Sichuan–Tibet Railway where excessively severe natural gradients must be overcome. It automatically finds an alignment optimized for the given objectives and complex constraints, as well as various promising alternatives.
Mountain Railway Alignment Optimization with Bidirectional Distance Transform and Genetic Algorithm
Various challenging constraints must be satisfied in railway alignment design for topographically complex mountainous regions. The alignment design for such environments is so challenging that existing methodologies have great difficulties in automatically generating viable railway alignment alternatives. We solve this problem with a hybrid method in which a bidirectional distance transform (DT) algorithm automatically selects control points before a genetic algorithm (GA) refines the alignment. This approach solves the problems of (1) determining the appropriate distribution of control points in the GA and (2) producing alignments that deviate significantly from the DT‐optimized paths. Automatic design of backtracking curves and dynamic generation of vertical points of intersection handling multiple constraints are developed to improve the GA performance. This method has been applied to a real case on the Sichuan–Tibet Railway where excessively severe natural gradients must be overcome. It automatically finds an alignment optimized for the given objectives and complex constraints, as well as various promising alternatives.
Mountain Railway Alignment Optimization with Bidirectional Distance Transform and Genetic Algorithm
Li, Wei (author) / Pu, Hao / Schonfeld, Paul / Yang, Junsheng / Zhang, Hong / Wang, Lei / Xiong, Jiaxing
2017
Article (Journal)
English
BKL:
56.00