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 being current solving systems suffering 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 solver 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.
翻译:量子计算是一个新兴的范例,在目前的科技界中,这种模式正在获得大量支持。广度地设想,量子计算作为下一个计算领域,其开发的起点仍然是其目前开发的在性能和能力方面受到重大限制的解决系统;研究人员和从业人员设计了一些有趣的方法,以克服这些障碍,这是量子古典混合算法,是最经常使用的解决方案之一。本文件的主要目标是扩大最近提议的混合量子计算-Tabau搜索阿尔哥里特姆(Tabau Search Algorithm)的结果和结果,以便分解问题。为了做到这一点,我们集中研究如何将这一方法适应于当前非对称旅行推销员问题的系统。总的来说,我们利用属于TSPLIB的六种著名案例,评估Quantum计算机- Tabu Search Algorithm(与QBSOLv(一个最先进的解析解析软件)的性能。此外,这项工作还假设了Asymital Travelrical Exportal Export Proport Proportal Projective Produstrical Projects, 将Alishal 用于整个Alistrual Clistal Exlistrual 和我们公司数据库的升级的系统。