Exact and heuristic methods for optimization in distributed logistics

Increasing sustainability in the transportation and logistics sector is a key element in achieving energy transition goals set internationally (UN), continentally (EU), and nationally. This thesis discusses two challenges related to this energy transition.
First, I study how offshore wind can become an attractive alternative to traditional energy producers. I investigate how the maintenance of offshore wind farms can be organized more efficiently. Think of smartly coordinating technicians, maintenance tasks, spare parts, and a fleet of vessels. Our new algorithms ensure that the relatively polluting visits to the wind farm can be reduced, which directly causes a reduction of CO2 emmision and an increased sustainable energy production.
Second, I focus on a different sustainability challenge in the logistics sector: How to handle the enormous amounts of product returns from and to (web)shops. We study how to incorporate these product returns in regular operations, instead of treating them distinct from current operations. In this way, we can reuse already existing capital, leading significant cost decreases. This directly increases sustainability of the e-commerce sector.
Although both challenges are structurally different from a practical point of view, from an applied mathematician’s perspective this is not true. Our smart plannings algorithms are broadly applicable, and can be used to resolve major questions on how to increase sustainability in the transportation and logistics sector.