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.
Speed
The Gurobi Optimizer is more than 50% faster than the solver of our closest competitor.
Robustness
The Gurobi Optimizer is tested on a wide range of difficult problems from many industries.
Support
Our world-class team – nearly 35% of which is comprised of PhDs – is dedicated to producing the best mathematical optimization solver technology and providing the best support.
Customers
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.
Financial Services
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.
Switching to Gurobi from CPLEX
Customers have told us that, once you understand a few key concepts, the migration process from CPLEX to Gurobi is straightforward and typically quite quick. In this page, we take you through the steps to migrating from CPLEX™ to Gurobi including:
- Building the model
- Setting Solver Parameters
- Computing and Extracting the Solution
In addition, you can also see a list of code examples, across a range of programming languages, on our code examples page.
Switching to Gurobi from Open Source Solvers
We know there are a range of solvers, free and paid, to choose from. We also know that for some situations a free solver might be all that you need. We can help you better understand your choices among free solvers, their relative performance, and some questions to ask yourself in deciding what type of solver is right for you. Specifically, on this page we cover the following topics:
- A list of some of the leading free linear and mixed-integer programming solvers
- Relative solver performance comparisons
- When a free solver may be the best choice
- A general comparison of free vs. commercial solvers
