Developing a Model for the Stochastic Time-Dependent Vehicle-Routing Problem

Vehicle-routing problems (VRP) have been studied in depth. Many variants of the problem exist, most of them trying to find a set of routes with the shortest distance possible for a fleet of vehicles. This paper combines two important variants, the stochastic VRP and the time-dependent VRP, to form and define the Stochastic Time-Dependent VRP. An efficient heuristic that is a new variant of the well-known saving algorithm is introduced. The algorithm incorporates simulation that enables an estimate of each route's probability of being the quickest. This new algorithm yields fast results that are 10% higher than optimal solutions. Such results are similar to the performance of the saving algorithm when compared to the capacitated VRP.