Transportation and delivery make up a significant portion of the cost of many products. As society’s demands become more complex and fast-paced, optimizing route logistics can result in huge savings for many companies. In recent years, researchers have been inspired by quantum computing to create better optimization algorithms now, and even better ones in the future as quantum technology matures.
What is the fastest route to take, the most efficient employee schedule, or the financial portfolio with the least amount of risk? Optimization is the science of finding the best solutions among many possibilities.
Making the best possible decisions is critical to the success of most businesses. This is particularly relevant today because companies have access to a large amount of high-quality data and they are interested in using this data to drive their decision making. The science of optimization can help businesses find the best solution among all possible solutions to maximize their performance and minimize their costs.
Many problems in finance take the form of mathematical optimization problems. As an example from portfolio optimization, an asset manager may be tasked with allocating funds across a pool of assets while maximizing the return at a given level of risk. However, conventional approaches often fail when computational resources cannot handle the amount of “noisy” real-world data (i.e., useful data that is corrupted or distorted by other, meaningless data), or extrapolating for missing data, or account for the correlations between all assets.
Quantum computing research and experimentation continues to make progress towards addressing complex computational problems. These include modelling systems in nature as they relate to chemistry and physics. Beyond this, quantum computing research has also shown promise in tackling problems in logistics and finance.