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arXiv 1806.09285cs.DS
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旅行商问题和哈密尔顿圈问题的新基准集

A new benchmark set for Traveling salesman problem and Hamiltonian cycle problem

Pouya Baniasadi, Vladimir Ejov, Michael Haythorpe, Serguei Rossomakhine

摘要:

我们提出了一个基准集旅行商问题(TSP)的特点是不同于现有的基准集。特别是,我们专注于一个或多个国家的最先进的TSP算法被证明是具有挑战性的小实例。这些实例是基于哈密尔顿循环问题(HCP)的困难实例。这包括文献中的实例,特别修改的随机生成的实例,以及从其他困难问题转换为HCP而产生的实例。我们证明,这样的基准实例是有助于理解的弱点和优势的算法。特别是,我们进行了一个基准测试,这个新的基准测试集总共超过五年的CPU时间,比较TSP算法协和,链接林Kernighan,和LKH。我们还包括HCP启发式SLH的基准测试工作。讨论的好处,特别是考虑边远的情况下,特别是相对于大小是非常困难的情况下,也包括在内。

英文摘要:

We present a benchmark set for Traveling salesman problem (TSP) with characteristics that are different from the existing benchmark sets. In particular, we focus on small instances which prove to be challenging for one or more state-of-the-art TSP algorithms. These instances are based on difficult instances of Hamiltonian cycle problem (HCP). This includes instances from literature, specially modified randomly generated instances, and instances arising from the conversion of other difficult problems to HCP. We demonstrate that such benchmark instances are helpful in understanding the weaknesses and strengths of algorithms. In particular, we conduct a benchmarking exercise for this new benchmark set totalling over five years of CPU time, comparing the TSP algorithms Concorde, Chained Lin-Kernighan, and LKH. We also include the HCP heuristic SLH in the benchmarking exercise. A discussion about the benefits of specifically considering outlying instances, and in particular instances which are unusually difficult relative to size, is also included.

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