computer science

Gurobi Optimizer

Gurobi Optimizer is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Gurobi Optimizer rather than just read about it. In short: 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.

Key takeaways

Gurobi Optimizer belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Gurobi Optimizer to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Gurobi Optimizer from memory before moving on to harder problems.

Reference excerpt

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.

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. 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). 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. 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. Since 2019, Gurobi is used by National Football League (NFL) to build its game schedule each year. 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. In 2021, DoorDash used Gurobi, in combination with machine learning, to solve dispatch problems. 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.

References

Worked examples

Example 1 — a first encounter with Gurobi Optimizer

Start with the simplest possible case. Write down what Gurobi Optimizer claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Gurobi Optimizer before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Gurobi Optimizer ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Gurobi Optimizer

In research: Gurobi Optimizer appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Gurobi Optimizer in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Gurobi Optimizer is common in secondary-school and first-year university syllabi. It links to neighbouring topics Linear programming, Mathematical optimization software, Numerical software, so understanding it makes those chapters shorter.
In everyday life: Look for Gurobi Optimizer outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Gurobi Optimizer in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Gurobi Optimizer means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Gurobi Optimizer out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Gurobi Optimizer in simple terms?

Why does Gurobi Optimizer matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Gurobi Optimizer?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Gurobi Optimizer.