Shipping route optimization is a difficult challenge to solve because of the need must account for several real-world variables that each have multiple solutions like the capacity of each ship, scheduling and finding the best route to minimize distance travelled. And the recent Suez Canal incident has only intensified the importance of improving the process.
This is why ExxonMobil is working with IBM to address explore the role quantum computing can play in optimizing maritime and vehicle shipping routes, a complex optimization problem that can be applied across not only maritime, but other industries such as automotive and supply chain.
Simply put, the complex problems facing maritime shipping impacts the majority of the world's transportation elements from a supply chain perspective and represents trillions of dollars. Unfortunately, numerous constraints exist in terms of port arrivals and departures – and, if a route includes going through a critical path like the Panama Canal or Suez Canal, precision timing is crucial.
“Any kind of advantage they can achieve can be quite significant, not only in time to market, but also in terms of savings,” Jamie Thomas, general manager IBM Systems strategy and development, tells IndustryWeek. “While optimization problems are too difficult for classical computers to solve today, they are the ideal type of problem poised to be solved by quantum computing, which use an entirely new model of computing based on quantum physics, which can overcome the problem of multiple variables and provide the best answer.”
Using the open programming model Qiskit, these different optimization elements were applied against four different quantum variational algorithms IBM is working with in the context of quantum computing, explains Thomas. “This allowed ExxonMobil to explore how each of these algorithms would enable them to solve this particular problem more effectively than what it can accomplish on classical machines,” she says. “They were able to conclude as quantum matures, they definitely believe it can be used to solve these kinds of optimization problems for maritime shipping. They were the first to really invest in understanding this type of complex problem in the world of maritime shipping.”
Exploring use cases
As quantum continues to mature, Thomas is excited about the potentially huge impact it can have on materials science. “The ability to understand and create new materials that can perhaps solve problems in the world of like automotive transport, where we need to continue to look at materials for electric batteries,” she says. “Materials that can create less pollution in the manufacturing process, especially as organizations switch more to battery on the journey to solve climate change.”
Life sciences are also an area ripe with opportunity. “We were able to speed up the arrivals of these vaccines, frankly, because of the dramatic change in science combined with technology,” says Thomas. “If we were able to do some of the modeling quantum allowed us to do in terms of different compounds more quickly, we can significantly improve beyond even the world's largest supercomputers today.”
As with any evolving technology, hurdles still remain for quantum computing. Part of the challenge is getting organizations trained to use quantum to solve their most complex problems. “That is why we have embarked on such a significant journey on learning and outreach to educational institutions,” she says. “We have over 200 educational institutions working with us, we've created an open-source textbook for those organizations to start to train college students, and we've embarked on training high school students.”
The focus on education and awareness is crucial going forward. After all, “without training in parallel with technology maturity, organizations are not going to be ready and will not have access to the talent coming out of the academic institutions to actually achieve their goals,” says Thomas.