| Company type | Private |
|---|---|
| Industry | Mathematical Optimization, Prescriptive Analytics, Decision Intelligence |
| Founded | 2008 |
| Headquarters | Beaverton, Oregon |
Key people | Dr. Zonghao Gu, Dr. Edward Rothberg, and Dr. Robert Bixby |
| Website | https://www.gurobi.com/ |
Gurobi Optimizer is a prescriptive analytics platform and a decision-making technology developed by Gurobi Optimization, LLC. The Gurobi Optimizer (often referred to as simply, “Gurobi”) is a solver, since it uses mathematical optimization to calculate the answer to a problem.
Gurobi is included in the Q1 2022 inside BIGDATA “Impact 50 List” as an honorable mention.[1]
YouTube Encyclopedic
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2: What is Mathematical Optimization?
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Introduction to Mathematical Optimization with Gurobi Integer Programming
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Introduction to Mathematical Optimization with Gurobi Linear Programming Part 2
Transcription
History
Dr. Zonghao Gu, Dr. Edward Rothberg, and Dr. Robert Bixby founded Gurobi in 2008, coming up with the name by combining the first two initials of their last names.[2] Gurobi is used for linear programming (LP), quadratic programming (QP), quadratically constrained programming (QCP), mixed integer linear programming (MILP), mixed-integer quadratic programming (MIQP), and mixed-integer quadratically constrained programming (MIQCP).[3][4]
In 2016, Dr. Bistra Dilkina from Georgia Tech discussed how it uses Gurobi in the field of computational sustainability, to optimize movement corridors for wildlife, including grizzly bears and wolverines in Montana.[5]
In 2018, The New York Times reported that the U.S. Census Bureau used Gurobi to conduct census block reconstruction experiments, as part of an effort to reduce privacy risks.[6]
Since 2019, Gurobi is used by National Football League (NFL) to build its game schedule each year.[7][8]
In 2020, Gurobi has partnered with GE Digital GE Grid Solutions, the University of Florida, and Cognitive Analytics on a project for planning and scheduling day-ahead electricity supply.[9]
In 2021, DoorDash used Gurobi, in combination with machine learning, to solve dispatch problems.[10]
In 2023, Air France used Gurobi to power its decision-support tool, which recommends optimal flight and aircraft assignments and can take constraints like fuel consumption and an aircraft’s flying hours into account.[11][12]
References
- ^ Gutierrez, Daniel (2022-01-10). "The insideBIGDATA IMPACT 50 List for Q1 2022". insideBIGDATA. Retrieved 2023-04-26.
- ^ INFORMS. "Gurobi Optimization". INFORMS. Retrieved 2023-04-26.
- ^ Analytics, Opex (2019-11-13). "Optimization Modeling in Python: PuLp, Gurobi, and CPLEX". The Opex Analytics Blog. Retrieved 2023-04-26.
- ^ "Using the Gurobi Optimizer Solvers on the Eagle System". nrel.gov. Retrieved 2023-04-26.
- ^ "Computing cost-effective wildlife corridors". Mongabay Environmental News. 2016-11-11. Retrieved 2023-04-26.
- ^ Hansen, Mark (2018-12-05). "To Reduce Privacy Risks, the Census Plans to Report Less Accurate Data". The New York Times. ISSN 0362-4331. Retrieved 2023-04-26.
- ^ "Meet the minds behind the 2019 NFL schedule: Mike North and Charlotte Carey". NFL. Retrieved 2023-04-26.
- ^ "An Introduction to the National Football League Scheduling Problem using" (PDF). Carnegie Mellon University.
- ^ "High-Performance Computing Helps Grid Operators Manage Increasing Complexity | PNNL". pnnl.gov. Retrieved 2023-04-26.
- ^ Shenwai, Tanushree (2021-08-23). "How DoorDash Uses Machine Learning ML And Optimization Models To Solve Dispatch Problem". MarkTechPost. Retrieved 2023-04-26.
- ^ Lin, Belle. "Startups Want to Help Airlines Prevent Tech Meltdowns". WSJ. Retrieved 2023-06-23.
- ^ Lin, Belle. "Southwest Meltdown Shows Airlines Need Tighter Software Integration". WSJ. Retrieved 2023-06-23.
This page was last edited on 4 March 2024, at 23:49