Robust path choice in networks with failures

The problem of adaptive routing in a network with failures is considered. T he network may be in one of finitely many states characterized by different travel times along the arcs, and transitions between the states occur acco rding to a continuous-time Markov chain. The objective was to develop a rou ting strategy that minimizes the total expected travel time. Dynamic progra mming models and flow-oriented models were developed and analyzed in the un capacitated and the capacitated case. It is shown that the robust plan can be found from a special two-stage stochastic programming problem in which t he second-stage models the rerouting problem after the state transition in the network. The models are illustrated on an example of the Sioux Falls tr ansportation network. The computational results reveal striking properties of different routing policies and show that substantial improvements in bot h duration and size of jams can be achieved by employing robust strategies. (C) 2000 John Wiley & Sons, Inc.