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。对于某些类别的优化问题，人们普遍认为QOA相比当前最先进的解决方案能够显著提升运行时性能。随着量子计算机建设的最新进展进入工业化阶段，基于量子的优化算法变得愈发重要。近期QOA领域出版物数量的急剧增加表明，该主题在学术界和工业界的重要性日益增长。本文的研究目标如下：（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）描述并比较绝热优化和基于门的优化这两类基本算法，讨论其潜力与局限性；（3）同时，我们研究了预计未来在决策中使用QOA将受到显著影响的关键运筹学应用领域；（4）最后，从运筹学角度探讨了未来使用QOA所引发的当前影响。