Robust Adaptive Routing Under Uncertainty
Arthur Flajolet, Sébastien Blandin, Patrick Jaillet
Operations Research · 2018 · Volume 66 · Issue 1
Abstract
We consider the problem of finding an optimal history-dependent routing strategy on a directed graph weighted by stochastic arc costs when the objective is to minimize the risk of spending more than a prescribed budget. To help mitigate the impact of the lack of information on the arc cost probability distributions, we introduce a robust counterpart where the distributions are only known through confidence intervals on some statistics such as the mean, the mean absolute deviation, and any quantile. Leveraging recent results in distributionally robust optimization, we develop a general-purpose algorithm to compute an approximate optimal strategy. To illustrate the benefits of the robust approach, we run numerical experiments with field data from the Singapore road network. The e-companion is available at https://doi.org/10.1287/opre.2017.1662 .
Keywords
stochastic shortest path, Markov decision process, distributionally robust optimization
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