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arXiv cs/0204024cs.DScs.CC
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几何最大旅行商问题

The Geometric Maximum Traveling Salesman Problem

Alexander Barvinok, Sandor P. Fekete, David S. Johnson, Arie Tamir, Gerhard J. Woeginger, Russ Woodroofe

摘要:

我们考虑旅行商问题,当城市是R^d中的点,对于某些固定的d,距离根据几何距离计算,由一些范数确定。我们表明,对于任何多面体范数,找到一个最大长度的巡回赛的问题可以解决在多项式时间。如果假设算术运算需要单位时间,我们的算法运行时间为O(n^{f-2} log n),其中f是决定多面体范数的多面体的面数。因此,例如,我们有O(n^2 log n)算法的情况下,在平面上的点下的直线和Sup规范。这与在每种情况下找到最小长度的游览是NP难的事实相反。我们的方法可以扩展到更一般的情况下,准范数不一定是对称的单位球,其中我们得到的复杂度为O(n^{2f-2} log n)。对于f=4的二维度量的特殊情况(包括矩形和Sup范数),我们给出了一个运行时间为O(n)的简单算法。该算法不使用任何间接寻址,因此即使在排序需要Omega(n \log n)时间的基于比较的模型中,其运行时间仍然有效。该算法的基本机制提供了一些直观为什么多面体规范允许快速算法。作为对多面体范数的简单性结果的补充,我们证明了对于R^d中的欧氏距离,d>2,极大TSP是NP-困难的。这揭示了新的研究困难的欧几里德距离。

英文摘要:

We consider the traveling salesman problem when the cities are points in R^d for some fixed d and distances are computed according to geometric distances, determined by some norm. We show that for any polyhedral norm, the problem of finding a tour of maximum length can be solved in polynomial time. If arithmetic operations are assumed to take unit time, our algorithms run in time O(n^{f-2} log n), where f is the number of facets of the polyhedron determining the polyhedral norm. Thus for example we have O(n^2 log n) algorithms for the cases of points in the plane under the Rectilinear and Sup norms. This is in contrast to the fact that finding a minimum length tour in each case is NP-hard. Our approach can be extended to the more general case of quasi-norms with not necessarily symmetric unit ball, where we get a complexity of O(n^{2f-2} log n). For the special case of two-dimensional metrics with f=4 (which includes the Rectilinear and Sup norms), we present a simple algorithm with O(n) running time. The algorithm does not use any indirect addressing, so its running time remains valid even in comparison based models in which sorting requires Omega(n \log n) time. The basic mechanism of the algorithm provides some intuition on why polyhedral norms allow fast algorithms. Complementing the results on simplicity for polyhedral norms, we prove that for the case of Euclidean distances in R^d for d>2, the Maximum TSP is NP-hard. This sheds new light on the well-studied difficulties of Euclidean distances.

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