Choosing a Math Programming Solver
In this eBook, we guide you through the step-by-step process of choosing a mathematical programming solver – so that you can find the best solver for your business requirements.
In this “Choosing a Math Programming Solver” eBook, you will learn:
- The key criteria to consider when choosing a commercial or open-source solver – whether you’re starting a mathematical optimization project or already involved in one – including Budget and Licensing, Performance and Scalability, Professional Support, Active Development, Deployment, Ease of Use, and the Complexity of Switching.
- The common scenarios that indicate it’s time to switch to a more robust solver like Gurobi.
- How to successfully switch to Gurobi from your current solution.
New Directions for Optimization
In this video, Gurobi CEO and Co-founder Ed Rothberg discusses our motivations for some of the recent features we’ve added to the Gurobi Optimizer. We’ll then look at recent developments in the field and talk about how they are influencing our thinking about potential future directions.
Mathematical optimization is a well-established, essential technological tool in the financial services industry. For over 50 years, mathematical optimization technologies have been used by leading companies across the financial services ecosystem (including institutional and consumer banks, wealth management firms, hedge funds, insurance providers, and fintech players) to:
- Address a wide variety of complex business problems including portfolio optimization, cash management, trade settlement, and asset-liability management.
- Make optimal, data-driven decisions that deliver improved operational efficiency, profitability, and regulatory compliance as well as reduced risk and costs.