Combinatorial optimization problems have a critical impact on all industries: from smart grids management to portfolio optimization or logistics. Most of them are NP-complete and are thus hard to address both accurately and rapidly using classical optimization tools like exact solvers or heuristics. Quantum Computing could bring more efficient resolution methods for these problems. Xavier Geoffret, Atos Quantum Computing pre-sale leader and Sabine Keravel, Atos Quantum product manager will elaborate on how Atos can support organizations in exploring new resolutions path for their optimization use cases using two different approaches: gate-based Quantum Computing and Quantum Annealing. They will provide an overview of a practical optimization workflow relying on the Atos Quantum Learning Machine’s main features: a universal and accessible programming environment, hardware constraint optimizers, advanced noisy and noiseless simulation capabilities.