The Burrito Optimization Game introduces players to the power of optimization
BEAVERTON, Ore.–(BUSINESS WIRE)–Gurobi Optimization, LLC, creator of the world’s fastest mathematical optimization solver, announced the launch of their new educational game that aims to show players the power of optimization. The “Burrito Optimization Game” is a free, web-based app designed for data science and operations research students, as well as anyone who stands to benefit from mathematical optimization. In addition to demonstrating the value of optimization, the game also proves its difficulty, as well as the importance of algorithms and solvers in finding an optimal solution.
Gurobi created the Burrito Optimization Game in collaboration with Dr. Larry Snyder of Lehigh University, who explains that at the time he and Gurobi started work on the project, there were several other projects in the data science community that used the premise of locating a hypothetical new restaurant. The projects scored possible locations based on demographics, demand, and other data science factors.
“As optimizers, we know it can be easy to pick the single best location once you have a score, but if you need to pick five, ten, or fifty locations, especially when there are thousands to choose from, that becomes a very different kind of problem,” says Dr. Snyder. “So we decided to use this as a way to introduce the optimization story, hoping that the idea of first coming up with a score for each location and then putting that into an optimization context would resonate, even for data scientists who hadn’t seen the restaurant examples.”
Gurobi’s game is based on a classic facility location problem and allows players to choose the best locations for a “Guroble” food truck, with the goal of maximizing their total profit. For each level, players are presented with a new story, with added complexity, and a set of data to help them make decisions. The data provided typically includes the cost of each truck, the price of ingredients, and the total sales revenue for each burrito sold, as well as scenarios that will impact decision-making—such as disruptions in the burrito ingredient supply chain, or weather conditions that impact a customer’s willingness to travel.
Players can drag and drop their Guroble trucks around an illustrated map, where they can see how many customers are in each building. The closer the truck is to a building, the more customers from that building will be willing to walk to the truck to buy a burrito. Players can see how their profits adjust when they drag and drop the truck to a different location, highlighting the importance of trade-offs in complex decision-making.
Once a player is satisfied with their placement of the trucks, Gurobi will solve the problem and find the optimal solution within a fraction of a second. Players can then see how far they were from the optimal solution in terms of total profit.
The game also provides tips along the way to further the learning experience once players submit their solution. For example, players might be notified that a certain part of the city is underserved, or they’ll see a hint that their solution has the optimal number of trucks, but in the wrong locations.
In subsequent rounds, the game introduces uncertainties for an added challenge. Players need to build their solutions based off of forecasts rather than actual demand in this game—a concept that’s very familiar for data science students. For example, there might be 25 potential customers forecast in a building, but the actual amount could be off by up to five customers. Error bars indicate how far in either direction the actual demands might be.
“What we’re hoping to convey is that if you were to try optimization by trial and error, it’s not only tedious and time-consuming, but it’s also hard to make good decisions,” explains Dr. Snyder. “We also wanted to make clear that although optimization is hard, it’s a mature scientific field with robust commercial and open-source software that can solve these problems for us.”
“We launched this a little while ago, and the early feedback has been extremely positive,” explained Dr. Edward Rothberg, Chief Executive Officer and Co-founder of Gurobi Optimization. “One common response from optimization professionals is excitement about the prospect of having a simple, entertaining way to show the people they work with the sorts of problems optimization can solve and the power that it brings.”
The Burrito Optimization Game is available on Gurobi’s website, accompanied by a series of resources that highlight intended educational takeaways and explain how instructors can teach the game in a classroom setting or how players can use the game on their own.
About Gurobi Optimization
Gurobi produces the world’s fastest and most powerful mathematical optimization solver—the Gurobi Optimizer—which is used by leading global companies across more than 40 different industries to rapidly solve their complex, real-world problems and make automated decisions that optimize their efficiency and profitability. As the market leader in mathematical optimization software, we aim to deliver not only the best solver, but also the best support—so that companies can fully leverage the power of mathematical optimization (on its own or in combination with other AI techniques such as machine learning) to drive optimal business decisions and outcomes.
Founded in 2008, Gurobi has operations across the Americas, Europe, and Asia and has more than 2,500 customers globally including SAP, Air France, Uber, and the National Football League (NFL). For more information, please visit https://www.gurobi.com/ or call +1 713 871 9341.
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