While Artificial Intelligence (AI), Internet of Things (IoT), Blockchain, and other technologies dominate discussions and find wide-ranging applications in supply chain and logistics, quantum computing is quietly getting ready to step into the spotlight.

Though it’s not making a lot of headlines yet, DHL’s Logistics Trend Radar and leading tech providers forecast its arrival within 5 to 10 years. So, what’s interesting about quantum computing? And how might it reshape the way we manage our supply chains? Let’s find out together.

Quantum Computing Explained Simply

The Evolution of Computing Technology

In the early 20th century, mechanical calculators laid the groundwork for what we now know as modern computing. The breakthrough came in 1946 with the Electronic Numerical Integrator and Computer (ENIAC), marking the birth of electronic computing. As integrated circuits, microprocessors, and transistors developed over time, the number of personal computers increased dramatically by the 1980s. The internet connected us all, encouraging further innovation.

As computing technology advanced, supercomputers emerged with significantly greater processing power than general-purpose computers. They have become indispensable tools for major corporations and governments. Nvidia, a key player in the computing industry, recently introduced its latest “superchip” as part of the Blackwell series. These chips are specifically designed to meet the exceptional processing demands of the growing generative AI trend.

One of the significant challenges facing regular and super computing is the decreasing size of computer parts and chips, which are rapidly approaching the size of a few atoms. Inside these chips, tiny transistors serve as ON/OFF switches, controlling the flow of electrical current. They are essential for processing binary information, where data is represented as bits—each bit can be either a 0 or a 1.

As chip sizes shrink, the number of transistors packed onto them increases exponentially, allowing for more complex computations and improving overall performance. However, this trend presents a limit: at such minuscule sizes, transistors are susceptible to a phenomenon known as ‘Quantum Tunneling.’ This occurs when electrons surpass barriers they theoretically shouldn’t, potentially causing errors in data processing and compromising the reliability of computing systems.

Understanding Quantum Computing

And here is where quantum computing comes in. To make a long story short, while traditional computers operate based on bits that can represent either a 0 or a 1, quantum computers leverage the principles of quantum mechanics to use quantum bits, or qubits. Unlike classical bits, qubits can exist in multiple states (one and zero) simultaneously with a probability between the two values, thanks to a property called superposition. 

This unique capability allows quantum computers to perform an enormous number of calculations simultaneously, offering unprecedented speed, storage capacity, and energy efficiency.

Considering how traditional computers transformed our world with simple binary processing, the potential of quantum computing is staggering. It’s no wonder that major players like IBM, Google, and Microsoft are all racing to perfect this technology, recognizing its potential to shape the future of computing and ensure they remain at the forefront of innovation.

So, why does quantum computing matter for supply chains? And how will it change how we manage them in the future?

Quantum Annealing: A Game-Changer for Supply Chain Efficiency

Supply chain management is all about optimization – whether it’s minimizing costs, maximizing efficiency, or juggling multiple objectives simultaneously. An optimization method of quantum computing that has shown promising practical benefits for supply chains and organizations is quantum annealing.

In simple terms, quantum annealing is a technique used in quantum computing to solve optimization problems, especially those with a vast number of possible solutions, known as combinatorial problems. Technically speaking, it works by simulating the behavior of quantum particles as they seek the lowest energy state, which corresponds to the optimal solution of a given problem. Unlike classical computing methods, which can struggle with the complexity of combinatorial problems with large settings, quantum annealing can explore all possible solutions simultaneously and find the best one in a fraction of the time. 

Examples of combinatorial problems in supply chain management are the traveling salesman problem (TSP) and the vehicle routing problem (VRP) – these are exactly the kinds of problems quantum annealing excels at solving. And it does so blazingly fast, often in milliseconds for a very large amount of points, enabling businesses to make real-time decisions that can significantly impact their bottom line, adjusting quickly to today’s volatile, uncertain, complex, and ambiguous (VUCA) world.

Supply Chains of Tomorrow: Quantum Computing in Action

While quantum computing technology is still in its early stages and not yet ready for widespread commercial use in supply chains, it’s steadily gaining interest and hitting key milestones. Currently, quantum computers are still playing catch-up with traditional and supercomputers, but they’re on a path of continuous improvement.

In real-world scenarios, quantum computing is often used alongside artificial intelligence (AI) and machine learning (ML) algorithms. For instance, Groovenauts, Inc. and Mitsubishi Estate Co., Ltd collaborated to optimize waste collection routes in Tokyo’s Marunouchi area using the “MAGELLAN BLOCKS” platform. This unique cloud platform combines AI to predict waste generation and quantum computing to determine the most efficient collection routes.

Similarly, Volkswagen Group has leveraged quantum algorithms to optimize taxi routes in Beijing, partnering with D-wave’s quantum computer. While desktop computers can relatively quickly find optimal routes for a few delivery stops, quantum computing drastically speeds up the process for more complex scenarios involving numerous stops and additional parameters, which can take months or years for even a supercomputer to solve.

Quantum computing holds also promise for various other supply chain applications, including container optimization, rapid simulation, and beyond.

Conclusion

In summary, quantum computing holds immense promise for revolutionizing supply chain management. While still in its early stages, it has shown remarkable progress in a short period of time. As the technology advances, businesses can expect even greater efficiency and innovation in their supply chain processes. Moreover, with its potential to operate more energy-efficiently, the computer industry is racing to make quantum computers viable on a commercial scale. This is crucial, as some predictions suggest that by 2040, the demand for computing power may surpass our ability to supply it.