Sustainable Urban Deliveries – SUD

The project will study the various sustainable alternatives and the variables that can be integrated into multi-level modeling scenarios. This in-depth study at several levels (strategic, tactical, and operational) will require the development of new mathematical models and optimization approaches to solve the decision-making problems mentioned above.

Urban last mile deliveries are a key component of transport in cities. They are a major contributor to pollution and greenhouse gas emissions, and demand for deliveries is further increasing. Cities are limiting access for thermal powered delivery vehicles and are thereby encouraging the use of environmentally friendly delivery modes. In this project, we are considering the potential of novel urban delivery concepts and the underlying operational planning problems. These concepts are typically based on two-echelon delivery approaches where synchronization between larger vehicles and smaller (green) modes of transport is necessary to transfer goods. The green transport modes we plan to take into consideration are cargo-bikes, human porters as well as electric robots. These modes have smaller capacities and ranges as conventional delivery vans and thereby require a two-echelon delivery approach.
Recent research in this emerging field is mainly based on solving deterministic operational planning problems. However, in urban settings we are confronted with a highly dynamic and stochastic system, where traffic and delivery demands are fluctuating in the context of an on-demand economy. We therefore propose to investigate novel models and algorithms for solving dynamic versions of these specific two-echelon vehicle routing problems in a generic manner with the aim of applicability to the three abovementioned transport modes. A major modeling and algorithmic challenge is the synchronization aspect between the vans and the other transport modes in such a highly dynamic setting.
This project sets up a new collaboration between two research groups with proven expertise in urban multi-echelon distribution and deterministic and dynamic optimization approaches.