Structural properties of hard metric TSP inputs

Tobias Mömke
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引用次数: 2

Abstract

The metric traveling salesman problem is one of the most prominent APX-complete optimization problems. An important particularity of this problem is that there is a large gap between the known upper bound and lower bound on the approximability (assuming P 6= NP ). In fact, despite more than 30 years of research, no one could find a better approximation algorithm than the 1.5-approximation provided by Christofides. The situation is similar for a related problem, the metric Hamiltonian path problem, where the start and the end of the path are prespecified: the best approximation ratio up to date is 5/3 by an algorithm presented by Hoogeveen almost 20 years ago. In this paper, we provide a tight analysis of the combined outcome of both algorithms. This analysis reveals that the sets of the hardest input instances of both problems are disjoint in the sense that any input is guaranteed to allow at least one of the two algorithms to achieve a significantly improved approximation ratio. In particular, we show that any input instance that leads to a 5/3-approximation with Hoogeveen’s algorithm enables us to find an optimal solution for the traveling salesman problem. This way, we determine a set S of possible pairs of approximation ratios. Furthermore, for any input we can identify one pair of approximation ratios within S that forms an upper bound on the achieved approximation ratios.
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硬公制TSP输入的结构特性
度量旅行商问题是最突出的apx完全优化问题之一。该问题的一个重要特点是,在已知的逼近性上界和下界之间存在很大的差距(假设p6 = NP)。事实上,尽管经过了30多年的研究,没有人能找到比Christofides提供的1.5近似更好的近似算法。对于一个相关问题,即度量哈密顿路径问题,情况也是类似的,其中路径的起点和终点是预先指定的:迄今为止,由hoogevenen在大约20年前提出的算法给出的最佳近似比率是5/3。在本文中,我们对两种算法的组合结果进行了严密的分析。这一分析表明,这两个问题的最难输入实例的集合是不相交的,因为任何输入都保证允许两种算法中的至少一种实现显著改进的近似比。特别地,我们证明了任何输入实例都可以导致hoogevenen算法的5/3近似,从而使我们能够找到旅行推销员问题的最优解。这样,我们确定了一组可能的近似比对。此外,对于任何输入,我们都可以在S内确定一对近似比,这对近似比形成了一个上界。
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