Academic Awards 2024 booklet

91 From Chaos to Control: Effective Approaches for Addressing Demand Uncertainty in Vehicle Routing Despite the increased availability of data through sensors and other sources, real-world route planning often takes place before all details are revealed. In this dissertation, I propose and explore innovative and effective transportation solutions for routing under uncertainty in specific settings. First, I consider situations where vehicle restrictions prohibit deliveries to customers with large and polluting vehicles, e.g., in city centers. One solution here is the use of a two-tiered distribution network. Trucks transport the orders from distribution centra to parking spots near the restricted area, where the orders are then transferred to smaller vehicles that perform the final deliveries. I show that by accounting for the uncertain customer demands during the construction of the delivery. Next, I consider the possibility of partially satisfying customer demands. Fairness plays an important role here: in humanitarian logistics, it is often of utmost importance that all locations receive some goods, rather than one location receiving everything, and arriving empty-handed at the remaining locations. I show that the integration of routing and allocation decisions yields better results in terms of fairness, efficiency, and cost-effectiveness when compared to the sequential approach of first routing and then allocating.