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Algorithms for most reliable routes on stochastic and time-dependent networks

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  • Arun Prakash, A.

Abstract

This study presents algorithms to determine the most reliable routes on stochastic and time-dependent networks. The measure of reliability adopted is the probability of on-time arrival at the destination, given a threshold arrival-time. We propose two distinct algorithms to determine optimal time-adaptive strategy and optimal apriori path on stochastic and time-dependent networks. First, a decreasing order-of-time algorithm is proposed to determine the optimal strategy to the sink from all node and departure-time combinations. Second, a label-correcting, network pruning algorithm is proposed to determine the optimal path between the source and the sink for a given departure-time. The correctness of both the proposed algorithms is proved and their computational complexity expressions are derived. The efficacy of the proposed procedures is demonstrated on large-scale transportation networks. This work has the potential to facilitate wider application of stochastic and time-dependent networks in reliability-based modeling and analysis.

Suggested Citation

  • Arun Prakash, A., 2020. "Algorithms for most reliable routes on stochastic and time-dependent networks," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 202-220.
    • Handle: RePEc:eee:transb:v:138:y:2020:i:c:p:202-220
    DOI: 10.1016/j.trb.2020.05.013
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