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arXiv 1101.5641math.CO
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图卵石化的一种线性最优化技术

A linear optimization technique for graph pebbling

Glenn Hurlbert

摘要:

图卵石是一种网络模型,用于研究给定的离散卵石供应是否可以通过卵石移动满足给定的需求。在图的边缘上的卵石移动从一个端点取两个卵石,并将一个卵石放在另一个端点;另一个卵石在运输过程中丢失作为通行费。已经证明,决定一个供应是否能满足图上的需求是NP完全的。一个图的卵石数是最小的t,使得t个卵石的每一个供应都能满足一个卵石的每一个需求。判定pebbling数是否至多为k是n_2^P-完全的。在本文中,我们开发了一个工具,称为权函数引理,计算上界,有时精确值卵石数的协助下,线性最优化。有了这个工具,我们能够计算比以前的算法更大的图的卵石数,而且速度也更快。我们还获得了许多家庭的图形,在许多情况下,手,更简单,显着更短的证明比以前现有的参数(证书通常的大小最多的顶点数乘以最大程度),特别是对于高度对称的图形。在这里,我们将权函数引理应用到几个特定的图,包括Petersen,Lemke,第四弱Bruhat,Lemke平方,和两个随机图,以及一些无限的图族,如树,圈,圈的图幂,立方体,和一些广义Petersen和Coxeter图。这部分回答了Pachter等人的问题,通过计算周期的卵石指数到渐近小的范围内。可以想象,这种方法产生一个近似算法的图卵石。

英文摘要:

Graph pebbling is a network model for studying whether or not a given supply of discrete pebbles can satisfy a given demand via pebbling moves. A pebbling move across an edge of a graph takes two pebbles from one endpoint and places one pebble at the other endpoint; the other pebble is lost in transit as a toll. It has been shown that deciding whether a supply can meet a demand on a graph is NP-complete. The pebbling number of a graph is the smallest t such that every supply of t pebbles can satisfy every demand of one pebble. Deciding if the pebbling number is at most k is Π_2^P-complete. In this paper we develop a tool, called the Weight Function Lemma, for computing upper bounds and sometimes exact values for pebbling numbers with the assistance of linear optimization. With this tool we are able to calculate the pebbling numbers of much larger graphs than in previous algorithms, and much more quickly as well. We also obtain results for many families of graphs, in many cases by hand, with much simpler and remarkably shorter proofs than given in previously existing arguments (certificates typically of size at most the number of vertices times the maximum degree), especially for highly symmetric graphs. Here we apply the Weight Function Lemma to several specific graphs, including the Petersen, Lemke, 4th weak Bruhat, Lemke squared, and two random graphs, as well as to a number of infinite families of graphs, such as trees, cycles, graph powers of cycles, cubes, and some generalized Petersen and Coxeter graphs. This partly answers a question of Pachter, et al., by computing the pebbling exponent of cycles to within an asymptotically small range. It is conceivable that this method yields an approximation algorithm for graph pebbling.

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