Developing “Killer Apps” for Quantum Computing: Logistics, Supply Chain and Routing

By Kevin Jackson

For Quantinuum

The world is a lot smaller than it was in the previous century – or even in the previous decade. 

Customers are now accustomed to a wide variety of products that can be delivered from distributors all over the globe. While this is a great opportunity for suppliers, it also presents a challenge in the form of supply chain, logistics, routing, and optimization. 

How can distribution companies continue to serve the needs of their customers in the most efficient and effective way possible? This may seem like a simple question, but it becomes a complex computational problem when trying to account for all the variables that can occur within a distribution network. 

What’s more, classical computers simply cannot adequately perform this optimization calculation in real-world scenarios. Because of the number of variables, the math just runs too slow. 

That said, new work in quantum computing has shown promise in applications within the optimization field. To that end, we interviewed Quantinuum’s Megan Kohagen and Dr. Mattia Fiorentini to better understand how quantum computing could to optimized logistics and supply chains.

Kohagen and Fiorentini are participating in a panel about quantum computing at Manifest: The Future of Logistics conference this week in Las Vegas, Nev.

Beyond classical computing 

When it comes to optimization it is all about maximizing or minimizing an objective.  A good example is a company that delivers goods and products but owns a limited number of trucks. To improve efficiency and minimize costs, the company needs to maximize the number of objects its trucks carry and identify the shortest routes between deliveries.

“You have all these constraints, you have your objective, and you’ve got to make decisions,” said Kohagen, an optimization researcher. “The decisions end up being things like how many goods you are going to send between your distribution centers and your stores? Each of these optimization problems, even if you consider them separately, are hard problems. The technical term is that they’re (non-deterministic polynomial)-hard because you’re dealing with discrete things. For example, I can’t send half a T-shirt to my customer. I can only operate with whole integers.” 

Fiorentini expands on this: “In logistics, we cannot leave anyone behind. If we need to deliver medicine, we cannot decide ‘the villages with less than 1,000 people – we don’t supply them. There are too many, and not enough people live there’. That’s not an option in today’s world.”

Today’s computers struggle to solve these NP-hard optimization problems because of the number of ever-changing variables.  Consider the much-studied Traveling Salesperson Problem, which is often used to illustrate the complexity of managing logistics, routing, and supply chains.  

This is a theoretical problem where a machine is tasked with finding the shortest route between an identified list of cities that a “salesperson” must visit before returning to the point of origin. This problem is simple enough with only a few cities, but it becomes exponentially harder as more locations are added, and other factors such as multiple salespeople, weather conditions, and unforeseen events arise. 

Classical computers can solve this theoretical problem for a single salesperson traveling to thousands of cities. But this scenario is not realistic, and this is where classical computers begin to struggle.

“The Traveling Salesperson Problem is not very representative of what happens in the real world,” Kohagen said. “For example, with online ordering so prevalent, a retailer has orders coming in constantly. They must determine how to efficiently retrieve those items from the warehouse, pack them into the trucks, and then transport them to the customers.”

Today, the reality of an extended supply chain or distribution network is beyond what the best classical computer can solve. Quantum computers harness unique properties of quantum physics that enable them to examine all possible answers simultaneously and then concentrate the probable output of the computation onto the best option.

“Classical is a great technology, but it doesn’t cut it here,” said Fiorentini, who develops and tests quantum algorithms for optimization. “Quantum is the best alternative to classical computing that we have.“

The quantum computing opportunity

Optimization problems have long been viewed as “killer applications” for quantum computing and research conducted by Fiorentini, Kohagen and others has begun to prove that. 

Fiorentini believes it is time for decision makers to explore and invest in quantum-enabled solutions for optimization problems. “There are two decisions here for decision makers,” he said. “We either give up on the problem and say, ‘we’ll just do the best we can with a classical solution, or we start allocating a budget for really developing quantum technology.”

Quantum computing is expanding rapidly and is poised to disrupt markets such as optimization.  A similar situation is the power sector, which is experiencing major disruptions due to innovations in renewable energy resources, energy storage, and regulatory reform. 

Every technology has a tipping point, and all signs point to a current trend in quantum computing moving rapidly to real-world applications in optimization.

“There are a lot of algorithms being developed for optimization right now,” said Kohagen. “If you really want to advance your business with quantum methods for logistics or supply chain, this is the moment to start. Decision makers must act quickly. Those that seize the opportunity before others will have a major advantage over those who lag.”

“As quantum computers continue to scale in computational power, they’ll be able to handle increasingly complex calculations to deliver more robust and optimized supply chain solutions,” said Tony Uttley, President and COO of Quantinuum.

“We’re excited by the acceleration of our System Model H1 technologies, Powered by Honeywell. Measured in terms of qubit number as well as quantum volume, we’re meeting our commitment to increase performance by a factor of 10X each year,” he said. “Alongside other revolutionary advances such as real-time error correction, we look forward to supporting the commercialization of quantum applications that will change the way logistical challenges are met. In fact, within the coming few months we’ll be sharing more exciting news regarding our latest technological achievements.”

Want to learn about our work to develop quantum-enabled optimization solutions for companies? Click here.