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- W2346430980 abstract "Improving efficiency and effectiveness of train movements over the rail lines have gained importance from the perspectives of both railway infrastructure management and train operations. Different solution techniques, such as exact, tailor-made heuristics, and meta-heuristics, have been developed for various configurations of problem setups. Markov chain is a well-developed technique to handle various stochastic problems in practice. Despite of its wide usage in diverse fields, it is rare to find applications in railway operations, particularly in train scheduling problems. Train rescheduling may be modeled as a series of conflict resolution process, in which train meet/pass locations and times are shifted usually by changing the pre-defined settings. Each conflict resolved deteriorates the inferior train to be forced to stopped at a station or siding in favor of a priority train. Using the historical data of train dispatcher decisions for conflict resolutions in a particular rail line, it is possible to establish a transition matrix for conflict resolutions by using an appropriate operational measure, as being the states, such as the lateness or punctuality of trains. The kernel of any Markov chain model is the transition matrix. Given the current state of a train, it is possible to predict its future state after some number of conflicts it experiences by using the transition matrix developed. This prediction can then be used in conflict resolution decisions. An empirical study conducted provides encouraging results towards elaborating the Markov chain conflict resolution model for train rescheduling in breadth and depth for various problem domains." @default.
- W2346430980 created "2016-06-24" @default.
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- W2346430980 date "2016-01-01" @default.
- W2346430980 modified "2023-09-26" @default.
- W2346430980 title "A Markov Chain Model for Conflict Resolutions in Train Rescheduling" @default.
- W2346430980 hasPublicationYear "2016" @default.
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