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Fleets must make decisions to optimize their operations every day. Consider a company with 500 trucks that need to be loaded with 500 diverse orders, all within three hours each morning. Optimizing each truck to ensure accurate, rapid delivery is critical to customers, yet it’s hard to solve the complex computations required to select the most efficient loading every day.
Quantum computing is well on its way to providing the answer, and might be a new frontier in easing logistics management.
How Do Quantum Computers Work?
Quantum computers do not solve problems the same way as classical computers. Instead, they leverage unique properties to simulate real-world scenarios and conduct extremely complex computations more rapidly and accurately than is possible with classical computers.
Liscouski
Quantum computers operate in something called multi-dimensional space. Classical computers are two-dimensional, and thus can’t handle the large data volumes of many real world problems. Because quantum computers are not limited to two dimensions, they can better mirror the natural multidimensional state of the world we live in and handle problems that are exponentially more complex.
The reason that quantum computing is such a perfect fit for optimization problems is that while classical computers offer up only one ‘best’ answer, quantum computers provide multiple diverse results. For trucking companies, this means the ability to define the impact among different scenarios and choose the route best optimized for each situation — in a fraction of the time and with a fraction of the resources required by classical computers.
In plain English, that means a quantum computer can simulate all of the options for a transportation logistics problem, while adjusting to explore outcomes of different shifts and changes, just as the real world situation would change as a result of those shifts. Even better, a quantum computer can select all of the results that meet the requirements, not just a single “best” solution. This gives decision-makers much deeper insights that are necessary to meet business needs as things change or new priorities emerge.
Many of us have heard of the traveling salesman problem, which asks, “Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city?” When applied to truck routing and how to optimize the routes, as well as the trucks, the challenge is that traveling salesman problems like this grow exponentially in complexity. Routing problems are more constrained and complex for every variable (truck, route, driver, etc.) that you add.
For example, a traveling salesman problem that has 10 stops results in 3,628,800 route options, and pushing it up to 40 stops adds more zeros to the number than is suitable to print! Routing multiple trucks and packages is even more complex.
This is where quantum computers promise to take on the task of quickly producing multiple options to choose from, so that businesses can make the best decisions based on their goals and the current circumstances. For example, if a truck needed to reroute in real time due to a sudden traffic jam or if a customer changed or canceled an order while the truck was already out for delivery. Based on the current circumstance, you would be able to adjust the truck’s route and delivery schedule to stay on time.
Quantum Computing Reality
Quantum-powered insights are attainable today for exploration and planning, and production-type results using hybrid classical-quantum could be available as soon as 2023. Simultaneously, organizations can begin to explore the power of quantum computers to better prepare for a future of hybrid processing — a method of blending quantum and classical computers to solve problems leveraging the power of quantum in the most efficient and accelerated way.
Robert Liscouski is the president and CEO of Quantum Computing Inc., which accelerates the value of quantum computing for real-world business solutions.
