Optimizing Biomass Forecasting and Supply Chain: An Integrated Modelling Approach

The growing worldwide population and rapid technological breakthroughs have increased energy consumption, highlighting the need for renewable and eco-friendly energy sources. Biofuel uptake is difficult owing to high prices, requires significant government measures to compete with conventional fuels and biomass-to-biofuel conversion inefficiencies are problematic. This research shows how biofuels can alter sustainability and examine Gujarat’s biomass supply chain utilizing advanced forecasting and supply chain optimization methods. A dataset including 2148 unique locations spanning the years 2010 to 2017 was utilized, and afterwards subjected to clustering analysis resulting in the identification of eight different groups. The next two-year biomass production is projected utilizing AutoML techniques. Finally, the supply chain is optimized using Mixed Integer Linear Programming (MILP) in order to reduce both costs and carbon footprint, in accordance with the predicted value.