Gurobi Optimizer
{{Short description|Optimization solver}}
{{Infobox company
| name = Gurobi Optimizer
| type = Private
| industry = Mathematical Optimization, Prescriptive Analytics, Decision Intelligence
| founded = 2008
| hq_location = 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.{{Cite web |last=Gutierrez |first=Daniel |date=2022-01-10 |title=The insideBIGDATA IMPACT 50 List for Q1 2022 |url=https://insidebigdata.com/2022/01/10/the-insidebigdata-impact-50-list-for-q1-2022/ |access-date=2023-04-26 |website=insideBIGDATA |language=en-US}}
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 letters of their last names.{{Cite web |last=INFORMS |title=Gurobi Optimization |url=https://www.informs.org/Impact/O.R.-Analytics-Success-Stories/Industry-Profiles/Gurobi-Optimization |access-date=2023-04-26 |website=INFORMS |language=en-US}} 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).{{Cite web |last=Analytics |first=Opex |date=2019-11-13 |title=Optimization Modeling in Python: PuLp, Gurobi, and CPLEX |url=https://medium.com/opex-analytics/optimization-modeling-in-python-pulp-gurobi-and-cplex-83a62129807a |access-date=2023-04-26 |website=The Opex Analytics Blog |language=en}}{{Cite web |title=Using the Gurobi Optimizer Solvers on the Eagle System |url=https://www.nrel.gov/hpc/eagle-software-gurobi.html |access-date=2023-04-26 |website=nrel.gov |language=en}}
In 2016, Dr. Bistra Dilkina from Georgia Tech discussed how she uses Gurobi in the field of computational sustainability, to optimize movement corridors for wildlife, including grizzly bears and wolverines in Montana.{{Cite web |date=2016-11-11 |title=Computing cost-effective wildlife corridors |url=https://news.mongabay.com/2016/11/computing-cost-effective-wildlife-corridors/ |access-date=2023-04-26 |website=Mongabay Environmental News |language=en-US}}
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.{{Cite news |last=Hansen |first=Mark |date=2018-12-05 |title=To Reduce Privacy Risks, the Census Plans to Report Less Accurate Data |language=en-US |work=The New York Times |url=https://www.nytimes.com/2018/12/05/upshot/to-reduce-privacy-risks-the-census-plans-to-report-less-accurate-data.html |access-date=2023-04-26 |issn=0362-4331}}
Since 2019, Gurobi is used by National Football League (NFL) to build its game schedule each year.{{Cite web |title=Meet the minds behind the 2019 NFL schedule: Mike North and Charlotte Carey |url=https://www.nfl.com/videos/meet-the-minds-behind-the-2019-nfl-schedule-mike-north-and-charlotte-care-428501 |access-date=2023-04-26 |website=NFL. |language=en-US}}{{Cite web |title=An Introduction to the National Football League Scheduling Problem using |url=https://www.math.cmu.edu/~af1p/Teaching/OR2/Projects/P56/OR-Final-Paper.pdf |website=Carnegie Mellon University}}
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.{{Cite web |title=High-Performance Computing Helps Grid Operators Manage Increasing Complexity {{!}} PNNL |url=https://www.pnnl.gov/news-media/high-performance-computing-helps-grid-operators-manage-increasing-complexity |access-date=2023-04-26 |website=pnnl.gov|date=11 September 2020 }}
In 2021, DoorDash used Gurobi, in combination with machine learning, to solve dispatch problems.{{Cite web |last=Shenwai |first=Tanushree |date=2021-08-23 |title=How DoorDash Uses Machine Learning ML And Optimization Models To Solve Dispatch Problem |url=https://www.marktechpost.com/2021/08/23/how-doordash-uses-machine-learning-ml-and-optimization-models-to-solve-dispatch-problem/ |access-date=2023-04-26 |website=MarkTechPost |language=en-US}}
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.{{Cite web |last=Lin |first=Belle |title=Startups Want to Help Airlines Prevent Tech Meltdowns |url=https://www.wsj.com/articles/startups-want-to-help-airlines-prevent-tech-meltdowns-11673652512 |access-date=2023-06-23 |website=WSJ |date=14 January 2023 |language=en-US}}{{Cite web |last=Lin |first=Belle |title=Southwest Meltdown Shows Airlines Need Tighter Software Integration |url=https://www.wsj.com/articles/southwest-meltdown-shows-airlines-need-tighter-software-integration-11672687980 |access-date=2023-06-23 |website=WSJ |date=2 January 2023 |language=en-US}}