Simulation-optimisation of last-mile logistics decisions

This thesis focuses on the development of simulation and optimisation methods to support the decision-making process in last-mile logistics. Findings include that parking illegally balances the traffic flow and the additional cruising time, reinforcement learning can be applied to improve the decision-making process of vehicles and traffic flow and cruising time can be used to optimise the parking infrastructure.<p></p>