Company:Gurobi Optimizer

From HandWiki
Gurobi Optimizer
TypePrivate
IndustryMathematical Optimization, Prescriptive Analytics, Decision Intelligence
Founded2008
HeadquartersBeaverton, Oregon
Key people
Dr. Zonghao Gu, Dr. Edward Rothberg, and Dr. Robert Bixby
Websitehttps://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]

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 2022, CIOReview featured Gurobi and its impact on the telecommunications industry.[11]

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.[12][13]

References

  1. Gutierrez, Daniel (2022-01-10). "The insideBIGDATA IMPACT 50 List for Q1 2022" (in en-US). https://insidebigdata.com/2022/01/10/the-insidebigdata-impact-50-list-for-q1-2022/. 
  2. INFORMS. "Gurobi Optimization" (in en-US). https://www.informs.org/Impact/O.R.-Analytics-Success-Stories/Industry-Profiles/Gurobi-Optimization. 
  3. Analytics, Opex (2019-11-13). "Optimization Modeling in Python: PuLp, Gurobi, and CPLEX" (in en). https://medium.com/opex-analytics/optimization-modeling-in-python-pulp-gurobi-and-cplex-83a62129807a. 
  4. "Using the Gurobi Optimizer Solvers on the Eagle System" (in en). https://www.nrel.gov/hpc/eagle-software-gurobi.html. 
  5. "Computing cost-effective wildlife corridors" (in en-US). 2016-11-11. https://news.mongabay.com/2016/11/computing-cost-effective-wildlife-corridors/. 
  6. Hansen, Mark (2018-12-05). "To Reduce Privacy Risks, the Census Plans to Report Less Accurate Data" (in en-US). The New York Times. ISSN 0362-4331. https://www.nytimes.com/2018/12/05/upshot/to-reduce-privacy-risks-the-census-plans-to-report-less-accurate-data.html. 
  7. "Meet the minds behind the 2019 NFL schedule: Mike North and Charlotte Carey" (in en-US). https://www.nfl.com/videos/meet-the-minds-behind-the-2019-nfl-schedule-mike-north-and-charlotte-care-428501. 
  8. "An Introduction to the National Football League Scheduling Problem using". https://www.math.cmu.edu/~af1p/Teaching/OR2/Projects/P56/OR-Final-Paper.pdf. 
  9. "High-Performance Computing Helps Grid Operators Manage Increasing Complexity | PNNL". https://www.pnnl.gov/news-media/high-performance-computing-helps-grid-operators-manage-increasing-complexity. 
  10. Shenwai, Tanushree (2021-08-23). "How DoorDash Uses Machine Learning ML And Optimization Models To Solve Dispatch Problem" (in en-US). https://www.marktechpost.com/2021/08/23/how-doordash-uses-machine-learning-ml-and-optimization-models-to-solve-dispatch-problem/. 
  11. "Gurobi Optimization: Better Business Decisions with Mathematical Optimization" (in en). https://www.cioreview.com/gurobi-optimization. 
  12. Lin, Belle. "Startups Want to Help Airlines Prevent Tech Meltdowns" (in en-US). https://www.wsj.com/articles/startups-want-to-help-airlines-prevent-tech-meltdowns-11673652512. 
  13. Lin, Belle. "Southwest Meltdown Shows Airlines Need Tighter Software Integration" (in en-US). https://www.wsj.com/articles/southwest-meltdown-shows-airlines-need-tighter-software-integration-11672687980.