 Quantum computing has moved from early promises to real-world problems solving through public and industrial research funding and is likely to efficiently solve certain NP-hard optimization problems where classical approaches fail. This paper provides an entry point to quantum optimization by demonstrating advances in obstacles with a suitable use case, discussing problem formulation, available algorithms, benchmarking and recent breakthroughs, current status and future directions. This article was authored by Rondo Young, Nicholas Chancellor and Pascal Hafman.