This Review discusses quantum optimization, focusing on the potential of exact, approximate and heuristic methods, core algorithmic building blocks, problem classes and benchmarking metrics. The challenges for quantum optimization are considered, and next steps are suggested for progress towards achieving quantum advantage.
