The idea of using the principles of quantum mechanics for processing and storing information was first conceived by theoretical physicists and computer scientists. A conference in 1981 gathered these brilliant minds together to discuss this revolutionary concept which later gave birth to various quantum computing algorithms and actual quantum computers.
At present, quantum technology is gaining ground and has attracted the attention of investors. In 2022 alone, the seed funding for quantum technology startups is reported to be around $2.35 billion. With such high interest in quantum technology, breakthroughs and innovations can be expected in the next few years.
In this article, we will examine two innovative quantum computing solutions that address optimization problems in real-world applications in the transportation sector.
IBM | Quantum-Classical Solution Stack for Vehicle Routing Problem
In a recently published paper, IBM’s Eagle quantum computer demonstrated its ability to offer solutions for Ising models of ferromagnetism, encompassing low-level and high-level complexity models. This significant development attests to the current level attained by quantum computing in its practical application towards complex real-world issues.
In this patent application, IBM proposes a hybrid system of classical and quantum computers to tackle the real-world problem of vehicle routing related to cargo delivery by a fleet of vehicles. In the first stage of calculation, various factors such as package sizes and arrival times are fed into a classical computer for calculating all possible routes. In preparation for the next stage, the generated routes are divided into subgroups where the number of routes per subgroup is based on the capacity of the quantum computer. Lastly, each subgroup is then fed into a quantum computer to identify the most efficient combination of routes that will satisfy customer needs at the lowest cost possible.
US 2023/0177415 was filed on December 5, 2021 by International Business Machines Corporation.
SavantX | Shipping Container Scheduling Using Quadratic Unconstrained Binary Optimization
Shipping containers are typically unloaded from ships and organized into rows or columns in a container yard. Based on a schedule of pick-up, trucks may arrive at the yard at specific times to pick up the cargo. Within the yard, there are strategically placed port cranes that lift the cargo from its position in the yard onto trucks for transport to their final destinations.
The operation of a crane to lift cargo from the yard to a truck can both be time-consuming and costly. Inefficient crane operations often result in trucks waiting overnight in the yard for their turn to be loaded, leading to further delays and additional expenses. Unnecessary movements of the crane not only consume energy but also waste valuable financial resources. Bearing these challenges in mind, SavantX offers an optimization approach aimed at enhancing the efficiency of crane operation when it comes to loading cargo onto trucks from yards.
In this patent, an optimization algorithm run on a quantum computer is utilized to determine the queuing order for trucks awaiting loading by a particular crane. The algorithm considers both the cargo locations and their assigned trucks, ensuring efficient allocation. Additionally, it considers the path that the crane will take to locate and transport each cargo to its designated truck. By employing this optimization approach, effective coordination between cranes and trucks can be achieved in terms of sequencing as well as route planning.
US 11,663,687 was filed on September 21, 2021 and granted on May 30, 2023 to SavantX Inc.
More on quantum technology in our 2023 Technology Trends Report.
