A Railway Scheduling Method using Probabilistic Model Checking
Mohammadsadegh Mohagheghi1, Anahita Khademi2

1Mohammadsadegh Mohagheghi*, Department of Computer science, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran.
2Anahita Khademi, Department of Computer science, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran.
Manuscript received on September 23, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 6694-6698 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1980109119/2019©BEIESP | DOI: 10.35940/ijeat.A1980.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Trains scheduling is an important problem in railway transportation. Many companies use fixed train timetabling to handle this problem. Train delays can affect the pre-defined timetables and postpone destination arrival times. Besides, delay propagation may affect other trains and degrade the performance of a railway network. An optimal timetable minimizes the total propagated delays in a network. In this paper, we propose a new approach to compute the expected propagated delays in a railway network. As the main contribution of the work, we use Discrete-time Markov chains to model a railway network with a fixed timetable and use probabilistic model checking to approximate the expected delays and the probability of reaching destinations with a desired delay. We use PRISM model checker to apply our approach for analyzing the impact of different train scheduling in double line tracks.
Keywords: Discrete-time Markov chains, Probabilistic model checking, Railway transportation, Train scheduling.