Tata Steel: Streamlining Steel Production

Tata Steel uses Gurobi to create and run their own Coal Blending Optimisation Model (CBOM), potentially saving the company millions of pounds in the long term.
Swissport: Automating Airport Staff Scheduling

Discover how Swissport reduces planning costs and achieves significant time savings
SwissQuant: Portfolio Optimization

See how swissQuant quickly creates optimal portfolios for private bank clients.
Robeco: Investment Portfolio Optimization

Discover how global asset management firm Robeco uses Gurobi to optimize the construction and performance of its systematic fixed-income investment portfolios, which encompass around EUR 12.5 billion in assets.
RWTH Aachen University: Teaching

See how Aachen University is using Python and Gurobi to help teach optimization modeling to thousands of students.
RWTH Aachen University: Energy Hub Design Optimization

Discover how a web-based tool – developed by a research group at RWTH Aachen University and powered by the Gurobi Optimizer – enables users to optimally configure and design complex energy supply systems.
RITE Institute: Power Production

See how Gurobi is optimizing large-scale mathematical models for power production across multiple sources in response to global warming.
Portland Public Schools: Redistricting

See how Gurobi helped Portland Public Schools in setting school district boundaries.
Polymathian: Supply Chain Optimization in the Mining Industry

Learn how a decision support tool – built by Polymathian and powered by the Gurobi Optimizer – enabled a leading global mining company to generate optimal strategic plans that increase profit margins by 5%.
Polymathian: Multi-Utility Asset and Network Optimization

Energy and utility providers strive to satisfy customer demand in the most cost-effective manner possible. To achieve this goal, they need to be able to maximize the utilization of their assets – which can be a mix of generation technologies and fuel sources – and capitalize on real-time supply, demand, and price fluctuations across their operational networks.