PhD defence Y.N. (Ymro) Hoogendoorn

Brief summary on the aim of the doctoral thesis:

The vehicle routing problem is the problem of serving a set of customers with a fleet of vehicles such that the travel costs of those vehicles are minimized, while making sure each vehicle starts and ends at a central depot. Countless variants exist, each with numerous real-world applications. One such variant is the waste collection problem, whose importance grows together with our waste production. In this thesis, we focus on exact methodology for the vehicle routing problem with different levels of demand information. Exact algorithms can guarantee to find the optimal solution to a problem while heuristics do not. Finding the exact solution is of value when one wants to fully optimize a process, benchmark a heuristic or obtain an optimality gap. The three different levels of demand information considered are: deterministic, stochastic and sensor-driven. In the first level, customer demand is known exactly before routing. Therefore, routes can be constructed such that each vehicle carries exactly the load it needs to transport. In the second level, we only know the distribution of demand before routing. This means we can usually not prevent a stock-out, but we can route the vehicles such that the routing costs plus the expected costs of inevitable restocking trips to the depot are minimized. In the third level, sensors are present at some customers, allowing us to incorporate this information into our routing decision.