聚焦混合量子计算--禁忌搜索算法：非对称推销员问题的新结果
Focusing on the Hybrid Quantum Computing -- Tabu Search Algorithm: new results on the Asymmetric Salesman Problem
摘要：
量子计算是一种新兴的范式，在当前的科学和技术界聚集了大量的人气。量子计算被广泛认为是计算的下一个前沿，但它仍处于发展的黎明。因此，当前的求解系统在性能和能力方面受到显著的限制。为了克服这些障碍，研究人员和实践者已经设计了一些有趣的方法，量子经典混合算法是最常用的解决方案之一。本文的主要目标是扩展最近提出的混合量子计算-禁忌搜索算法的结果和发现的划分问题。为了做到这一点，我们专注于我们的研究适应这种方法的非对称旅行商问题。总体而言，我们采用了六个著名的实例属于TSPLIB评估性能的量子计算-禁忌搜索算法相比，QBSolv，一个国家的最先进的分解求解器。此外，作为一个额外的贡献，这项工作还假设使用量子计算为基础的方法的非对称旅行商问题的第一个解决方案。为了促进整个社区在QC方面的研究，我们已经将项目的资源库作为开源代码发布，以供进一步应用和改进。
英文摘要：
Quantum Computing is an emerging paradigm which is gathering a lot of popularity in the current scientific and technological community. Widely conceived as the next frontier of computation, Quantum Computing is still at the dawn of its development. Thus, current solving systems suffer from significant limitations in terms of performance and capabilities. Some interesting approaches have been devised by researchers and practitioners in order to overcome these barriers, being quantum-classical hybrid algorithms one of the most often used solving schemes. The main goal of this paper is to extend the results and findings of the recently proposed hybrid Quantum Computing - Tabu Search Algorithm for partitioning problems. To do that, we focus our research on the adaptation of this method to the Asymmetric Traveling Salesman Problem. In overall, we have employed six well-known instances belonging to TSPLIB to assess the performance of Quantum Computing - Tabu Search Algorithm in comparison to QBSolv, a state-of-the-art decomposing solver. Furthermore, as an additional contribution, this work also supposes the first solving of the Asymmetric Traveling Salesman Problem using a Quantum Computing based method. Aiming to boost whole community's research in QC, we have released the project's repository as open source code for further application and improvements.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
