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Home » Watch: Using Quantum Computing to Optimize Shipping Routes
VIDEO

Watch: Using Quantum Computing to Optimize Shipping Routes

March 14, 2021
Robert J. Bowman, SupplyChainBrain

A look at the innovative application of quantum computing to the problem of optimizing ship and vehicle routes, with Amy Herhold, Director of Physics and Mathematical Sciences, Corporate Strategic Research with ExxonMobil Research and Engineering, and Jamie Thomas, General Manager of IBM Systems Strategy & Development.

Quantum computing is still in its infancy, but it’s already being applied to some real-world problems that classical computing can’t handle, such as the optimal routing of Exxon’s ships. Elements include weather patterns, inventory levels and length of voyage. In the end, the number of variables involved in such calculations “can quickly swamp what you can do with a classical computer today,” says Herhold.

Artificial intelligence can help, but it needs the right data to feed it. “It comes down to looking across many decision variables and figuring out how to pick the right path,” Herhold says.

Thomas says quantum computing is “a marriage between information and quantum physics.” The combined properties of those disciplines allow users to hugely expand the “attack surface” of a problem — a accomplishment that Herhold calls “the big prize.” They can review many more variables and possibilities than are possible with classical computing. “Think of this as the 1950s all over again,” Thomas adds. “It’s a very different technology.”

Exxon’s use of quantum computing is still in the exploratory stage, says Herhold. Ultimately, the problem of ship routing will require larger quantum computers and accompany algorithms that can work with the greater number of variables. But the technology is already being applied to multiple industries, and can even be used in tandem with classical computing for decisions such as ship routing.

“We’re clearly a few years out from full production,” says Thomas. “What we’re seeing now is a massive amount of experimentation.”

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