Discrete optimization problems, which can be formulated as QUBO models, are ubiquitous in the telecommunications industry. Quantum Annealing is a promising optimization method with valuable real-world applications in this sector.
Indeed, as we will detail in this paper, many abstract combinatorial optimization problems have found concrete applications in optimizing telecommunications networks. What's more, in many practical cases, the size and connectivity of the network allow direct implementation of QUBO models on today'sQuantum Annealing machines, offering a fully quantum treatment of the problem. Alternatively, where this is not possible, powerful hybrid solvers can be used to solve large optimization instances of up to a million variables.