Mathematical Optimization + Machine Learning = Your Perfect AI Tech Team
“Mathematical Optimization and Machine Learning: Your Perfect AI Tech Team” – a Forrester Opportunity Snapshot commissioned by Gurobi Optimization – provides valuable insights on how mathematical optimization can be used on its own or in concert with machine learning to solve business problems.
In this custom study – conducted by Forrester Consulting – of U.S. managers who are responsible for or influence their organization’s data science or execution strategy, you will learn:
- How companies today are using mathematical optimization to solve complex problems, optimize operational processes, and make critical, data-driven business decisions.
- All about the business benefits that companies have realized as a result of using mathematical optimization.
- How companies are using machine learning to make accurate, data-driven predictions.
Why Should You Use Mathematical Optimization?
In this video, Gurobi CEO and Co-founder Ed Rothberg explains how mixed-integer programming (MIP) combines expressiveness and robustness to produce high-quality, reliable solutions.
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.