Elise Miller-Hooks

Learn More
We consider stochastic, time-varying transportation networks, where the arc weights (arc travel times) are random variables with probability distribution functions that vary with time. Efficient procedures are widely available for determining least time paths in deterministic networks. In stochastic but time-invariant networks, least expected time paths can(More)
Travel times in congested transportation networks are time-varying quantities that can at best be known a priori probabilistically. In such networks, the arc weights (travel times) are represented by random variables whose probability distribution functions vary with time. These networks are referred to herein as stochastic, time-varying, or STV, networks.(More)
In congested transportation and data networks, travel (or transmission) times are time-varying quantities that are at best known a priori with uncertainty. In such stochastic, time-varying (or STV) networks, one can choose to use the a priori least-expected time (LET) path or one can make improved routing decisions en route as traversal times on traveled(More)
In this paper, a pseudopolynomial time algorithm is presented for solving the integral time-dependent quickest flow problem (TDQFP) and its multiple source and sink counterparts: the time-dependent evacuation and quickest transshipment problems. A more widely known, though less general version, is the quickest flow problem (QFP). The QFP has historically(More)