Vehicle Routing with Departure Smoothing

This thesis investigates the vehicle routing problem with limited processing capacity at the depot. In this problem, there can only be a certain number of vehicles loading at the same time, depending on the number of loading docks available. Furthermore, there is also a constraint on the number of goods that can be loaded per time unit. We develop an adaptive large neighborhood search algorithm that, while constructing the vehicle routes, shifts the start times of the routes in a smart way, which we call departure smoothing, such that the processing capacity constraints are met. Computational experiments on both real-world and theoretical problem instances show that the algorithm performs well and is able to find good solutions in reasonable time. Finally, we also compare the method with a twophase approach, which first constructs the vehicle routes and applies departure smoothing afterwards. Experiments demonstrate that the integrated approach presented in this thesis obtains better solutions in less running time.