Stochastic Combinatorial Optimization Problems (SCOPs) are many times used to model more accurately realistic situations. However, the stochasticity introduced also perplexes the computation of the objective function making it either difficult to solve or in our case very timeconsuming. In this paper, we present different techniques of evaluating the objective function of the Orienteering Probl...

Vehicle routing problems (VRPs) are concerned with the design of efficient routes that deliver goods and services from (to) central depots to (from) customer locations, satisfying specific business constraints. In the last 50 years, a vast amount of research has been devoted to solve different VRP variants. Nonetheless, most of the solution methods for VRPs are based on the premise that problem...

We study optimal routing policy problems in stochastic time-dependent networks, where link travel times are modeled as random variables with time-dependent distributions. These are fundamental network optimization problems for a wide variety of applications, such as transportation and telecommunication systems. The routing problems studied can be viewed as counterparts of shortest path problems...

In practically all real-world planning and scheduling problems one is faced with uncertainty. Usually this uncertainty is abstracted away during the modeling process, such that standard combinatorial optimization algorithms can be used to solve the problem. This abstraction step is necessary, because these algorithms generally cannot deal with uncertainty. In this thesis we study the Vehicle Ro...

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 be determined by setting each random ...

We consider finding static yet robust recurring milk-run tours while dynamically routing the vehicle between site visits. The network arcs experience recurrent congestion, leading to stochastic and time-dependent travel times. Based on vehicle location, time of day, and current and projected network congestion states, we generate dynamic routing policies (DRP) for every pair of sites using stoc...