Harnessing Inferior Solutions For Superior Outcomes: Obtaining Robust Solutions From Quantum Algorithms
Pascal Halffmann, Michael Trebing, Steve Lenk
In the rapidly advancing domain of quantum optimization, the confluence of quantum algorithms such as Quantum Annealing (QA) and the Quantum Approximate Optimization Algorithm (QAOA) with robust optimization methodologies presents a cutting-edge frontier. Although it seems natural to apply quantum algorithms when facing uncertainty, this has barely been approached.
arXiv:2404.16784•Genetic and Evolutionary Computation Conference Companion (GECCO Companion)•Jul 14, 2024•1 citation