Reverse supply chain of residual wood biomass

Sustainability and environmental consciousness is becoming an increasingly important issue, and questions of recycling and reuse are getting more and more attention lately. While biomass is an important renewable resource and can take many forms (ranging from agricultural residues to food waste, forestry residues and construction/wood processing residues), biomass wastes are predominantly considered for the production of bioenergy. However, depending on the exact type of biomass residual, alternatives might also exist for its use that are significantly less studied. For example, the management of residual wood biomass is an important field, and not many studies have dealt with it besides its use for bioenergy. There are multiple different problem classes that can be studied in the reverse logistics processes of wood. Optimizing the activities of this supply chain and identifying their special characteristics is a relevant issue both for reducing environmental impact and for increasing the efficiency and profit of companies. The aim of this project is to study the possible alternative reverse logistics processes of biomass residuals, concentrating on woody residuals as a use-case. We plan to identify the crucial optimization problems connected to the collection, sorting, transportation, warehousing and processing of this biomass, and provide efficient models and algorithms for their solution. We will explore new approaches based on hybrid algorithms and machine learning.