混合量子计算--禁忌搜索算法在划分问题中的应用：旅行商问题的初步研究
Hybrid Quantum Computing -- Tabu Search Algorithm for Partitioning Problems: preliminary study on the Traveling Salesman Problem
摘要：
量子计算被认为是计算的下一个前沿，它吸引了当前科学界的大量关注。这种计算为研究人员提供了解决复杂优化问题的革命性范例，提供了显着的速度优势和有效的搜索能力。无论如何，量子计算仍处于发展的初级阶段。因此，现有的体系结构存在一定的局限性，这也是本文研究的动机。本文提出了一种新的求解方案--混合量子计算-禁忌搜索算法.所提出的方法的操作的主要支柱是对量子资源的访问的更大控制，以及大量减少非盈利访问。为了评估我们的方法的质量，我们使用了7个不同的旅行推销员问题的例子作为基准集。所获得的结果支持了初步结论，即我们的算法是一种为解决划分问题提供有希望的结果的方法，同时它大大减少了对量子计算资源的访问。我们还通过开发一种进化的多形式多任务算法作为初始化方法，为转移优化领域做出了贡献。
英文摘要：
Quantum Computing is considered as the next frontier in computing, and it is attracting a lot of attention from the current scientific community. This kind of computation provides to researchers with a revolutionary paradigm for addressing complex optimization problems, offering a significant speed advantage and an efficient search ability. Anyway, Quantum Computing is still in an incipient stage of development. For this reason, present architectures show certain limitations, which have motivated the carrying out of this paper. In this paper, we introduce a novel solving scheme coined as hybrid Quantum Computing - Tabu Search Algorithm. Main pillars of operation of the proposed method are a greater control over the access to quantum resources, and a considerable reduction of non-profitable accesses. To assess the quality of our method, we have used 7 different Traveling Salesman Problem instances as benchmarking set. The obtained outcomes support the preliminary conclusion that our algorithm is an approach which offers promising results for solving partitioning problems while it drastically reduces the access to quantum computing resources. We also contribute to the field of Transfer Optimization by developing an evolutionary multiform multitasking algorithm as initialization method.
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。
