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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/6210

Title: A decision support system to improve service quality in multimodal rapid rail systems: A bayesian perspective
Authors: Ugurlu, S
Aktas, E
Topcu, I
Keywords: Multi-criteria decision making
Real life applications
Transportation and traffic
Publication Date: 2011
Publisher: International Conference on Computers and Industrial Engineering
Citation: Computers & Industrial Engineering, Los Angeles: 872 - 877, 23 - 26 Oct 2011
Abstract: In this study, the accessibility of the rail transit stations in a multimodal network formed by a trunk line and its feeder lines are defined. Connectivity between lines and the accessibility of the nodes identify the overall spatial structure of the network. The factors influencing the access choices of rail transit stations and satisfaction of transit travelers in rapid rail transit systems are investigated in order to gain insights into the factors and their interrelationships. The quantitative indications of the relationships are produced and the complexity of evaluating the performance of transit services is exhibited. As the interrelationships are mainly stochastic, the problem on hand is treated as a Bayesian Belief Network (BBN). A BBN approach that presents a learning mechanism is employed and is used as an alternative decision making tool to analyze the rapid rail transit services and identify policies to improve the traveler’s level of service.
Description: Copyright @ 2011 International Conference on Computers and Industrial Engineering
URI: http://bura.brunel.ac.uk/handle/2438/6210
ISSN: 2164-8689
Appears in Collections:Business and Management
Brunel Business School Research Papers

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