Finding the most efficient way to transport items across a network like the U.S. highway system or the Internet is a problem that has taxed mathematicians and computer scientists for decades.

To tackle the problem, researchers have traditionally used a maximum-flow algorithm, also known as “max flow,” in which a network is represented as a graph with a series of nodes, known as vertices, and connecting lines between them, called edges.

Given that each edge has a maximum capacity—just like our highways and the fiber-optic cables used to transmit data—such algorithms attempt to find the most efficient way to send goods from one node in the graph to another, without exceeding limitations.

But as the size of networks like the Internet has grown exponentially, it’s often prohibitively time-consuming to solve constraint problems using traditional computing techniques, according to Jonathan Kelner, an associate professor of applied mathematics at MIT.

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