DECISION SUPPORT FOR VEHICLE ROUTING IN REALITY

Abstract

This thesis studies problem variants of the vehicle routing problem (VRP) under various conditions and presents solutions to help decision makers under various scenarios in practice. The priority-based unmanned combat aerial vehicle (UCAV) routing problem, which considers both munitions delivery and targets assignment, is a generalization of classical VRP. When unmanned aerial vehicles (UAVs) fly over threat zones, the UAV attrition is taken into account, and the routes of UAVs are dynamically adjusted accordingly. In practice, the fleet of vehicles comprises heterogeneous vehicles. The solution to the VRP with a heterogeneous fleet and time windows determines the type and number of vehicles to employ with a minimal cost. Uncertainties may make originally feasible solutions infeasible. The solutions to VRP with time windows (VRPTW) with stochastic travel and service times and VRPTW with stochastic demands tackle the common uncertainties in VRP.