TSP和HCP基准集

本文介绍了一个针对旅行商问题（TSP）和哈密顿循环问题（HCP）的新基准集。该基准集专注于小型实例，这些实例对现有的TSP算法构成挑战。数据集包括来自文献的实例、特别修改的随机生成实例以及从其他困难问题转换而来的实例。这些基准实例有助于理解算法的弱点和优势。数据集的创建旨在通过提供具有不同特征的实例，评估TSP算法的有效性，并揭示算法在特定情况下的性能差异。

This paper presents a novel benchmark set for the Traveling Salesman Problem (TSP) and the Hamiltonian Cycle Problem (HCP). This benchmark set focuses on small-scale instances that present challenges to state-of-the-art TSP algorithms. The dataset comprises instances sourced from existing literature, specially modified randomly generated instances, and instances converted from other computationally hard problems. These benchmark instances enable researchers to gain insights into the strengths and weaknesses of algorithms. The dataset is developed to evaluate the efficacy of TSP algorithms by providing instances with varied characteristics, and to reveal the performance discrepancies of algorithms under specific circumstances.