Planning of production networks for alternative fuels

You will learn to set up a suitable MILP model for integrated location, capacity and technology planning for synthetic fuels under abstracting assumptions, to implement it in Python and to solve it using the Gurobi solver, as well as to derive recommendations for action by analyzing the optimization results. You will use the generic OR model of the Warehouse Location Problem and learn to adapt it to a subject-specific model.

The project "OR4Sustainability" has also created further offers: 

Case Study "Selections of optimal power plant generation mix"

Case Study "Novel flexibility options in the German electricity grid"

"Multi-objective planning of production networks for alternative fuels"

"Planning of production networks for alternative fuels under uncertainty"

Case Study "Application of real options analysis for investment in energy sector"

Case Study "Exploring possibilities for decarbonising households' energy demans"

Case Study "Application of real options analysis for repowering of wind power plants"

Case Study "Life cycle assessment and multi-criteria evaluation using the example of a wind turbine"