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Quantum Computing and the Suez Canal

9
September
,
2021
Yuval Boger

On March 23, 2021, the Ever Given container ship became wedged in the Suez Canal, blocking all maritime traffic. It remained stuck for six days until partially released. A day before its release, over 350 ships were waiting to pass through the Canal, delaying nearly $10B worth of cargo.

The Suez Canal connects the Red Sea with the Mediterranean. It is one of the world’s busiest waterways, providing a preferred alternative to other water routes or - as was the case before the Canal opened in the 19th century - of offloading cargo, ferrying it by land, and loading on ships waiting in the other sea.

But what happens when the Canal is closed? Shipping companies must decide what to do next: wait? Turn around? Choose alternative routes?

Shipping decisions are complex, and so are ground- and air-based shipping. Which ship to send where? In what order should a ship - or a UPS truck - visit its destinations? Those decisions depend on many variables: the distance between the various destinations, the cost of travel, the risk of delays and more. Different companies might make different decisions with the same data depending on what they wish to optimize for: cost, time, minimal fuel consumption, minimal risk, fewest cargo carriers and so forth.

This class of problems is often called the Traveling Salesperson Problem (TSP), envisioning a salesperson that needs to make multiple sales calls. Computationally, it is a difficult problem to solve and is one of the most studied problems in optimization.

Quantum computers can help. Algorithms such as Quantum Approximate Optimization Algorithm (QAOA) allow quantum computers to solve TSP and other combinatorial optimization problems much faster than their classical counterparts.

Why is that important? Because just like in the Suez Canal example, the inputs are dynamic. Routes are blocked or congested, the price of fuel fluctuates, the desired routes change and so forth. The ability of a shipping company to dynamically optimize its routes can be of great financial significance. Imagine, for instance, if FedEx found a way to reduce its costs by 15% using quantum computers, or if Uber gained a competitive advantage over Lyft by employing quantum. This is one reason why quantum computing is considered a strategic technology in supply chain and many other applications.


On March 23, 2021, the Ever Given container ship became wedged in the Suez Canal, blocking all maritime traffic. It remained stuck for six days until partially released. A day before its release, over 350 ships were waiting to pass through the Canal, delaying nearly $10B worth of cargo.

The Suez Canal connects the Red Sea with the Mediterranean. It is one of the world’s busiest waterways, providing a preferred alternative to other water routes or - as was the case before the Canal opened in the 19th century - of offloading cargo, ferrying it by land, and loading on ships waiting in the other sea.

But what happens when the Canal is closed? Shipping companies must decide what to do next: wait? Turn around? Choose alternative routes?

Shipping decisions are complex, and so are ground- and air-based shipping. Which ship to send where? In what order should a ship - or a UPS truck - visit its destinations? Those decisions depend on many variables: the distance between the various destinations, the cost of travel, the risk of delays and more. Different companies might make different decisions with the same data depending on what they wish to optimize for: cost, time, minimal fuel consumption, minimal risk, fewest cargo carriers and so forth.

This class of problems is often called the Traveling Salesperson Problem (TSP), envisioning a salesperson that needs to make multiple sales calls. Computationally, it is a difficult problem to solve and is one of the most studied problems in optimization.

Quantum computers can help. Algorithms such as Quantum Approximate Optimization Algorithm (QAOA) allow quantum computers to solve TSP and other combinatorial optimization problems much faster than their classical counterparts.

Why is that important? Because just like in the Suez Canal example, the inputs are dynamic. Routes are blocked or congested, the price of fuel fluctuates, the desired routes change and so forth. The ability of a shipping company to dynamically optimize its routes can be of great financial significance. Imagine, for instance, if FedEx found a way to reduce its costs by 15% using quantum computers, or if Uber gained a competitive advantage over Lyft by employing quantum. This is one reason why quantum computing is considered a strategic technology in supply chain and many other applications.


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