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
The Open Group Launches the Open Footprint® Standard, Edition 1.0 to Streamline Scope 1, 2, and 3 Emissions Management2.6.2026 09:00:00 CEST | Press release
The Open Group, the vendor-neutral technology and standards organization, today announced the release of the Open Footprint® Standard, Edition 1.0, that will help organizations streamline scope 1, 2, and 3 emissions reporting. The new standard is the first open emissions data model to address all three scopes, providing a comprehensive framework that enables organizations to collect and standardize data from their value chain and report across multiple jurisdictions. “There is an urgent need to streamline emissions data management and reduce the manual effort required to capture data within supply chains, perform data conversion, and report out to various regulators,” said Steve Nunn, President and CEO of The Open Group. “The Open Footprint Standard removes friction and lowers cost, helping organizations identify emissions reduction opportunities.” Key features of the model include: Standardized emissions data definitions and relationships Simplified emissions data sharing and interope
Thredd Renews and Expands Partnership with Caxton2.6.2026 09:00:00 CEST | Press release
Five-year renewal and strategic expansion strengthens travel, corporate, and parent-child card innovation Thredd, the AI-first issuer processing platform, today announced a five-year renewal and strategic programme expansion with Caxton, the leading payments solutions provider, reinforcing Thredd’s role as the company’s primary issuer-processor across consumer and corporate cards. Caxton, a leading UK payments provider, has partnered with Thredd since 2020 to power its multi-currency prepaid travel and expense cards. Customers can hold up to 15 currencies on a single card. As part of the renewed agreement, Thredd will bring Caxton’s parent-child card programme, nimbl, onto the Thredd platform. All nimbl customers will be re-carded as the programme is launched using Thredd’s infrastructure, with completion targeted before the end of the year. nimbl is a financial education-focused debit card designed for children aged 6–16, enabling parents to manage allowances and teach money managemen
Medscape Brings AI to the Hematology Frontline at EHA 20262.6.2026 08:00:00 CEST | Press release
Landmark symposium to equip clinicians with practical, ethical AI frameworks, chaired by a lead author of Europe's ESMO EBAI and ELCAP oncology guidelines. Medscape Education will launch Future-Ready Hematologists: Practical and Ethical Use of AI in Hematology and Oncology at EHA 2026 on June 11, where leading experts will convene to explore responsible AI in one of medicine's most complex, rapidly evolving specialties. Registration is free for all EHA delegates. Reserve your seat here. The session is chaired by Prof. Jakob N. Kather, MD, MSc, Else Kroener Fresenius Center for Digital Health, Technical University Dresden, and NCT, University Hospital Heidelberg. He is joined by Prof. Chan Cheah, MBBS, DMSc, Consultant Hematologist, Sir Charles Gairdner Hospital, Perth, Australia; and Prof. Matthew Lunning, DO, FACP, Chief of Hematology and Assistant Vice Chancellor of Research, University of Nebraska Medical Center. Hematology moves faster than any clinician can track alone. AI can clo
Signaloid Announces Preview of New ASIC Targeted at Physical AI and Robotics Applications2.6.2026 06:00:00 CEST | Press release
Signaloid previews a new ASIC purpose-built for physical AI and robotics workloads.The chip, taped out with TSMC in partnership with IC-Link by imec and Cadence, is projected to deliver up to 1000× better performance-per-watt in key physical AI workloads. Signaloid (https://signaloid.com), a computing platform company providing hardware and binary-translation-based acceleration of AI, robotics, aerospace, and quantitative finance workloads, today announced the tapeout and preliminary specifications documents for its C0-ASIC. Delivery of engineering samples to the first customer is due in Q3 2026 and additional FPGA-based systems implementing the ASIC’s design are under discussion for deployment in the UK and Switzerland later in 2026. The C0-ASIC was targeted specifically at energy-efficient physical AI workloads. The UK Advanced Research and Invention Agency (ARIA) will take delivery of systems based on the ASIC for use in next-generation AI workloads such as second order methods. “Th
Blackstone Raises its Largest Asia Private Equity Fund at $13.1 Billion2.6.2026 03:00:00 CEST | Press release
Oversubscribed Fund More than Doubles Capital Raised for Predecessor Vehicle Blackstone (NYSE: BX) today announced the final close of Blackstone Capital Partners Asia III (“BCP Asia III”) at $13.1 billion, exceeding its $10 billion target and marking the firm’s largest private equity fundraise in the region. The oversubscribed fund reached its hard cap and builds on the strong performance of the strategy’s first two vintages, with this close representing more than double the amount of capital raised for its predecessor vehicle. Joe Baratta, Global Head of Blackstone Private Equity Strategies,said: “We are grateful for the continued trust of our investors in Blackstone and our leading Asia Private Equity franchise. This successful fundraise reflects the strength of our platform and our ability to perform through cycles. Asia Pacific is the fastest-growing region in the world, presenting compelling opportunities to invest at scale behind our high-conviction themes and deliver for our inv
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
