OR-GUROBI-OPTIMIZATION
14.11.2022 15:01:59 CET | Business Wire | Press release
Gurobi Optimization, LLC, the leader in decision intelligence technology, today announced the release of Gurobi Optimizer 10.0. This release provides customers with a boost to its already industry-leading speed, the ability to embed machine learning models directly into Gurobi optimization models, and new tools for model development, monitoring, and advanced diagnosis—so users can solve new types of problems, even faster than before.
Performance Improvements and Advanced Solving Techniques
The Gurobi R&D team continues to push the boundaries of performance—resulting in improvements to existing algorithms and the development of several brand-new techniques. As a result, Gurobi Optimizer 10.0 has achieved the following performance improvements since the release of Gurobi Optimizer 9.5:
Type |
Algorithm |
Overall speed-up |
On >100sec models |
LP |
Concurrent |
10% |
25% |
Primal Simplex |
3% |
10% |
|
Dual Simplex |
3% |
10% |
|
MIP |
MILP |
13% |
24% |
Convex MIQP |
57% |
2.4x* |
|
Convex MIQCP |
28% |
88%* |
|
Non-Convex MIQCP |
51% |
2.6x |
|
*MIQP and MIQCP hard model test sets are smaller than for other problem classes. |
|||
“We’ve achieved a more than 75x speedup on MILP since version 1.1. But more importantly, Gurobi 10.0 can now solve even more models easily, including some models that were, until now, intractable,” explained Dr. Tobias Achterberg, Vice President of Research and Development at Gurobi Optimization.
Gurobi 10.0 also includes the following advances in the underlying algorithmic framework:
- New network simplex algorithm – Greatly speeds up solving LPs with network structure.
- New heuristic for QUBO models, which can arise in quantum optimization – Improves Gurobi's ability to quickly find good feasible solutions for quadratic unconstrained Boolean optimization problems.
- Significant performance gains on MIPs that contain machine learning models – Results in a more than 10x improvement on certain models that contain embedded neural networks with ReLU activation functions.
- New optimization-based bound tightening (OBBT) algorithm – Greatly speeds up solving nonconvex MIQCP models.
- Reorganized concurrent LP solver – Improves performance and reduces memory footprint.
Innovative Data Science Integration
With Gurobi Machine Learning—an open-source Python project to embed trained machine learning models directly into Gurobi—data scientists can more easily tap into the power of mathematical optimization.
Specifically, Gurobi Machine Learning allows users to add a trained machine learning model as a constraint to a Gurobi model (e.g., from scikit-learn, TensorFlow/Keras, or PyTorch). Thus, users can estimate a real-world system by training a machine learning model, and then use this machine learning model as a constraint in Gurobi, in order to optimize controls on that system.
“We’re aiming to connect the world of data science with the world of optimization. With Gurobi, you can take your machine learning ‘black box’ that’s generating your predictions and plug it directly into your optimization model—enabling you to connect your forecasting with optimization,” explained Achterberg.
With this release, we're also making it more convenient to integrate gurobipy model building with pandas objects through a new, dedicated open-source package. (Available on GitHub/PyPI in Q4 2022.)
Enterprise Development and Deployment Experience
To make its solver even more accessible and easy to use, the Gurobi team has integrated new tools for model development, monitoring, and advanced diagnosis:
- Significant enhancements to the matrix-friendly API in gurobipy – All matrix-friendly modeling objects now support multiple dimensions, and dimension handling leans consistently on NumPy, including broadcasting.
- New logistic general constraint – Makes it easy to incorporate a constraint in MIP that models the logistic function.
- NuGet package for .NET – Allows .NET users to download Gurobi directly from the NuGet server.
- Memory limit parameter that allows graceful exit – Users can set a memory limit and still get the best solution and resume the optimization after the limit was hit.
- New Compute Server dashboards – The Gurobi Compute Server now includes two new dashboards, enabling users to monitor metrics over time and drill down to the actual activity to better understand the cluster usage and application behavior.
- Expanded platform support – Gurobi 10.0 includes support for Python 3.11 and Linux on ARM 64-bit.
Gurobi introduced its Web License Service (WLS) for Docker and Kubernetes container environments last year, with the release of Gurobi 9.5. With Gurobi 10.0, the team has expanded WLS to support nearly all types of containerized environments. Moreover, customers can now also obtain WLS licenses that allow them to run Gurobi in virtually all deployment scenarios, including containerized environments, virtual machines, and bare-metal machines, across Linux, macOS, and Windows.
“Our customers love our WLS and the flexibility it provides. And now they can dynamically deploy Gurobi software in even more environments,” explained Duke Perrucci, Gurobi’s Chief Operating Officer.
Additionally, starting with Gurobi 10.0, major product releases—and their subsequent minor and technical product releases—will be supported for a term of three years from the initial major product release date. For example, Gurobi version 10.0.0 (released in November 2022) and minor releases between 10.0 and 11.0 will be supported until November 2025.
“This helps create predictability for our customers, so they know exactly how long a version will be supported,” explained Dr. Sonja Mars, Director of Optimization Support at Gurobi Optimization. “We aim to deliver expert technical guidance and support for our customers—and this policy helps eliminate the guesswork. We want our customers to get the help they need, when they need it.”
Dr. Edward Rothberg, Chief Executive Officer and Co-founder of Gurobi Optimization added, “We have the absolute best minds in optimization here at Gurobi. Across every department, you’ll find people who aren’t just smart—they’re also deeply committed to our customers and to providing the best possible experience. I’m proud to be a part of this team.”
To learn more about Gurobi 10.0, please visit gurobi.com/whats-new-gurobi-10-0/.
About Gurobi Optimization
With Gurobi’s decision intelligence technology, you can make optimal business decisions in seconds. From workforce scheduling, portfolio management, and marketing optimization, to supply chain design, and everything in between, Gurobi identifies your optimal solution, out of trillions of possibilities.
As the leader in decision intelligence, Gurobi delivers easy-to-integrate, full-featured software and best-in-class support, with an industry-leading 98% customer satisfaction rating.
Founded in 2008, Gurobi has operations across the Americas, Europe, and Asia. Over 2,500 global customers across 40+ industries run on Gurobi, including SAP, Air France, and the National Football League, as well as half of the Fortune 10 and 70% of top global tech companies. For more information, please visit https://www.gurobi.com/ or call +1 713 871 9341.
To view this piece of content from cts.businesswire.com, please give your consent at the top of this page.
View source version on businesswire.com: https://www.businesswire.com/news/home/20221114005243/en/
About Business Wire
Subscribe to releases from Business Wire
Subscribe to all the latest releases from Business Wire by registering your e-mail address below. You can unsubscribe at any time.
Latest releases from Business Wire
TestMu AI Introduces the Source-to-Verdict Loop in Kane CLI, Carrying Every Requirement to a Ship Decision With Portable Proof23.7.2026 15:45:00 CEST | Press release
Kane CLI now takes a requirement all the way to a ship-or-hold verdict, designing the tests, running them in a real browser, and emitting an open .evidence proof pack that teammates, AI agents, and auditors can all verify, with no server or dashboard required TestMu AI (formerly LambdaTest), the world's first Agentic AI-powered Quality Engineering platform, introduced a source-to-verdict loop in Kane CLI, its natural-language testing tool. Building on Kane CLI's evolution from a browser automation tool, the loop carries a product requirement to a ship decision, writing the tests, running them in the local browser, collecting the proof, measuring coverage from what actually happened, and returning a verdict. As AI agents write, run, and fix tests, a green checkmark is no longer enough: a step that checks nothing passes, a test written against a spec that changed weeks ago passes, and an agent that says “done” without the click ever landing passes. Empty green and earned green are the sa
Norway’s health system adopts Wolters Kluwer UpToDate Enterprise Edition23.7.2026 15:30:00 CEST | Press release
Enterprise Clinical Decision Support solution available to 30,000 clinicians in more than 50 Norwegian hospitals Wolters Kluwer Health announced that Norway’s health system has renewed its adoption of UpToDate Enterprise Edition, a market-leading Clinical Decision Support (CDS) solution, for its nationwide health system which includes over 50 public hospitals and 11,000 beds in over 20 trusts. This extends a 15 year partnership with Helsebiblioteket, now part of the Norwegian Institute of Public Health (NIPH). Helping clinicians on a national scale Kjell Tjensvoll, Team Leader for Helsebiblioteket said, ‘‘Providing frontline teams with easy access to the latest medical knowledge is vital in reducing unwarranted variation and improving patient care on a national scale. UpToDate Enterprise Edition enables this, and we are delighted to strengthen our relationship with Wolters Kluwer and provide continued support for clinicians across the country.’’ UpToDate Enterprise Edition was selected
Boyd Watterson Global Names John Creswell Global Chief Client Officer to Accelerate Global Growth and Client Engagement23.7.2026 15:00:00 CEST | Press release
Veteran investment management executive will lead global sales, client engagement and marketing as Boyd Watterson Global continues expanding its global alternatives platform across real estate, infrastructure, and debt strategies. Boyd Watterson Global today announced the appointment of John Creswell as Global Chief Client Officer, a newly created senior leadership role that reflects the firm's continued investment in growth and its evolution into a leading global alternatives investment platform. This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20260722823117/en/ John Creswell has joined Boyd Watterson Global as Global Chief Client Officer, a newly created role overseeing global sales, client engagement and marketing across the U.S., Europe and APAC. In this role, Creswell will oversee global sales, client engagement and marketing efforts across the United States, Europe and APAC, helping investors access the firm's capabilitie
Trulioo Launches AI Agent to Resolve Beneficial Ownership Where Global Registries Fall Short23.7.2026 15:00:00 CEST | Press release
Breakthrough AI agent reconstructs ownership for long-tail businesses and hard-to-reach jurisdictions while significantly increasing UBO coverage Trulioo, a global risk intelligence platform, today announced the UBO Discovery Agent, the newest layer in Trulioo's UBO Discovery capability inside its business risk and Know Your Business (KYB) verification workflow. AI is reshaping fraud, making it easier for bad actors to hide, and harder for companies to catch them. This makes the already tough job of verifying who actually owns a business even more difficult. Determining a business's ultimate beneficial owner is an ongoing, acute challenge for companies: registry coverage is inconsistent across countries, and even where registries exist, they typically record shareholders and directors of record (rather than the people actually in control). That data isn't simply outdated, it reflects a structural lag: ownership changes and time passes before the filing is made and processed, so a looku
Humanoid Raises $152 Million at $1.35 Billion Post-Money Valuation, Becoming Europe's First Pure-Play Humanoid Robotics Unicorn23.7.2026 15:00:00 CEST | Press release
Humanoid announces its Series A investment round, reaching a $1.35 billion valuation just two years after founding.It is the largest ever Series A for a humanoid-first robotics company in Europe, positioning Humanoid as the leading humanoid-first robotics unicorn in the UK and continental Europe.The new capital will accelerate Humanoid's next-generation robot development, commercial deployments with global industrial leaders, and evolution of the proprietary AI platform on the path toward general-purpose humanoids.The investment marks a defining moment for Europe's tech ecosystem, showing that globally competitive Physical AI companies can be built and scaled in Europe. Humanoid, a UK-based AI and robotics company building industrial humanoid robots, announced a $152 million Series A financing at a $1.35 billion post-money valuation. This funding brings the total amount raised to date to $270 million. The round was led by Prime Movers Lab, a venture capital firm focused on investments
In our pressroom you can read all our latest releases, find our press contacts, images, documents and other relevant information about us.
Visit our pressroom
