The goal of this project is to analyze how companies can make better decisions when designing and managing supply chain networks within the circular economy. These decisions occur on three interrelated levels. At the strategic level, firms determine the location and capacity of warehouses and production facilities. At the tactical level, they plan material and product flows within the resulting network. Finally, at the operational level, they make day-to-day decisions such as vehicle routing and scheduling. The shift from a linear to a circular economy fundamentally alters these decisions by introducing reverse logistics, material recovery, and recycling processes. Moreover, choices made at one level directly constrain and shape the options available at the subsequent levels. To address this multi-level and interdependent planning problem, the project plans to apply integrated methods that consider the effects of decisions on the subsequent levels. These methods are based on constrained clustering, stochastic optimization and dynamic programming and are intended as a decision support tool.

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