Combinatorial optimisation is a very common problem in economics. We can think, for example, of problems such as finding the shortest route through certain cities or maximising efficiency in the production process by optimally planning the set of processes involved. Often, finding the best choice among a large number of possible combinations is not an easy task for traditional computing. Quantum computing, however, offers new tools with the potential to offer better performance in solving these problems. Among the quantum technologies used for combinatorial optimisation, adiabatic quantum computation, and in particular quantum annealing, is undoubtedly the most successful approach to date. If you want to know more about this technology and its implications in this kind of problems, you can read our white paper.
In previous posts, we have discussed the optimisation of portfolios using quantum annealing. Now, we will examine an alternative approach within a gate-based quantum computer, providing a view to understanding how QAOA works and a practical use case for the top ten enterprises in IBEX 35.
In a previous post, we discussed how quantum annealing is an efficient technique for finding global minima in complex optimization problems. Now, we will take a step further by introducing reverse annealing, a powerful variation that enhances the search process by starting from a known solution and refining it through local exploration.
Have you ever wondered if it is possible to make money by exchanging currencies? Believe it or not, the answer is yes! This is possible because exchange rates are fixed by currency pairs and sometimes when considering more than two currencies, we can find a sequence of exchanges that allows us to make money by returning to the initial currency.