highlights We present algorithms to determine the most reliable strategy and path on stochastic and time-dependent networks. The measure of reliability chosen is the on-time arrival probability at the destination. We present a decreasing order-of-time algorithm for optimal time-adaptive strategy and a pruning algorithm for optimal path. We derive the correctness of the proposed procedures and show their efficacy on large-scale transportation networks.

    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.


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    Title :

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


    Contributors:


    Publication date :

    2020-05-28


    Size :

    19 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English