Abstract
We study the problem of maximizing the probability of arriving on time in a stochastic network. Nodes and links in the network may be congested or uncongested, and their states change over time and are based on states of adjacent nodes. Given a source, destination, and time limit, the goal is to adaptively choose the next node to visit to maximize the probability of arriving to the destination on time. We present a dynamic programming solution to solve this problem. We also consider a variation of this problem where the traveler is allowed the option to wait at a node rather than visit the next node. For this setting, we identify properties of networks for which the optimal solution does not require revisiting nodes.
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Christman, A., Cassamano, J. (2013). Maximizing the Probability of Arriving on Time. In: Dudin, A., De Turck, K. (eds) Analytical and Stochastic Modeling Techniques and Applications. ASMTA 2013. Lecture Notes in Computer Science, vol 7984. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39408-9_11
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DOI: https://doi.org/10.1007/978-3-642-39408-9_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39407-2
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