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Reliability evaluation of a multistate railway transportation network from the perspective of a travel agent

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  • Yeh, Cheng-Ta
  • Lin, Yi-Kuei
  • Yeng, Louis Cheng-Lu
  • Huang, Pei-Tzu

Abstract

Travelling by railway trains is usually the preferred option of travelers. Assessing whether a railway company can provide sufficient seats or cabins is meaningful for a travel agent to evaluate how the size of a tour group they can serve. A railway transportation system presents a set of available trains connecting the starting station and the destination station for a tour group according to their itinerary and the train timetable of a railway transportation company. The railway transportation system can be represented as a network with arcs denoting trains and nodes denoting starting, destination, and transfer stations. Because the available seats or cabins (i.e., capacity) in a train may be partially or fully reserved by other agents or groups, the capacity should be stochastic. Accordingly, the system can be modeled as a multistate railway transportation network. System reliability is defined as the probability that a tour group can successfully travel from the starting station to the destination station according to their itinerary, and can be a decision indicator for the travel agent. This study proposes an algorithm based on minimal paths to evaluate the system reliability. A case study of the railway transportation system in Taiwan is analyzed to demonstrate the applicability and computational efficiency of the proposed algorithm.

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  • Yeh, Cheng-Ta & Lin, Yi-Kuei & Yeng, Louis Cheng-Lu & Huang, Pei-Tzu, 2021. "Reliability evaluation of a multistate railway transportation network from the perspective of a travel agent," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    • Handle: RePEc:eee:reensy:v:214:y:2021:i:c:s0951832021002866
    DOI: 10.1016/j.ress.2021.107757
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    7. Forghani-elahabad, Majid & Yeh, Wei-Chang, 2022. "An improved algorithm for reliability evaluation of flow networks," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    8. Huang, Cheng-Hao & Huang, Ding-Hsiang & Lin, Yi-Kuei, 2023. "Network reliability prediction for random capacitated-flow networks via an artificial neural network," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
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