Quantum optimization algorithms (QOAs) have the potential to fundamentally transform the application of optimization methods in decision making. For certain classes of optimization problems, it is widely believed that QOA enables significant run-time performance benefits over current state-of-the-art solutions. With the latest progress on building quantum computers entering the industrialization stage, quantum-based optimization algorithms have become more relevant. The recent extreme increase in the number of publications in the field of QOA demonstrates the growing importance of the topic in both the academia and the industry. The objectives of this paper are as follows: (1) First, we provide insight into the main techniques of quantum-based optimization algorithms for decision making. (2) We describe and compare the two basic classes of adiabatic and gate-based optimization algorithms and argue their potentials and limitations. (3) Herein, we also investigate the key operations research application areas that are expected to be considerably impacted by the use of QOA in decision making in the future. (4) Finally, current implications arising from the future use of QOA from an operations research perspective are discussed.

翻译：量子优化算法（QOAs）有望从根本上改变优化方法在决策中的应用方式。对于某些类别的优化问题，普遍认为 QOA 相比当前最先进的解决方案能显著提升运行时性能。随着量子计算机的最新进展进入工业化阶段，基于量子的优化算法变得更具现实意义。近期 QOA 领域出版物数量的激增，凸显了该主题在学术界和工业界日益增长的重要性。本文目标如下：（1）首先，我们深入探讨基于量子的优化算法在决策中的主要技术；（2）描述并比较绝热量子优化和门模型量子优化这两类基本算法，探讨其潜力与局限性；（3）进一步研究预计未来 QOA 在决策中应用将显著影响的关键运筹学应用领域；（4）最后，从运筹学视角讨论未来使用 QOA 所引发的当前启示。