OPTIMIZATION OF RAILWAY OPERATIONS USING NEURAL NETWORKS
Document Type
Journal Article
Publication Date
1996
Subject Area
land use - planning, ridership - commuting, mode - rail
Keywords
Train operation, Train handling, Railways, Railroads, Optimization, Optimisation, Network analysis (Planning), Artificial intelligence
Abstract
In this paper, neural networks (an empirically-based AI approach) are examined for obtaining good solutions in short time periods for the train formation problem (TFP). Following an overview, and formulation of railroad operations, a neural network formulation and solution to the problem are presented. First a training process for neural network development is conducted followed by a testing process that indicates that the neural network model will probably be both sufficiently fast, and accurate, in producing train formation plans.
Recommended Citation
Martinelli, D, Teng, H, (1996). OPTIMIZATION OF RAILWAY OPERATIONS USING NEURAL NETWORKS. Transportation Research Part C: Emerging Technologies, Volume 4, Issue 1, p. 33-49.
Comments
Transportation Research Part C Home Page: http://www.sciencedirect.com/science/journal/0968090X