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A Generic Approach to Decomposition Algorithms, with an Application to Digraph Decomposition

机译:分解算法的通用方法及其在有向图分解中的应用

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A set family is a collection of sets over a universe. If a set family satisfies certain closure properties then it admits an efficient representation of its members by labeled trees. The size of the tree is proportional to the size of the universe, whereas the number of set family members can be exponential. Computing such efficient representations is an important task in algorithm design. Set families are usually not given explicitly (by listing their members) but represented implicitly. We consider the problem of efficiently computing tree representations of set families. Assuming the existence of efficient algorithms for solving the Membership and Separation problems, we prove that if a set family satisfies weak closure properties then there exists an efficient algorithm for computing a tree representation of the set family. The running time of the algorithm will mainly depend on the running times of the algorithms for the two basic problems. Our algorithm generalizes several previous results and provides a unified approach to the computation for a large class of decompositions of graphs. We also introduce a decomposition notion for directed graphs which has no undirected analogue. We show that the results of the first part of the paper are applicable to this new decomposition. Finally, we give efficient algorithms for the two basic problems and obtain an σ(n~3)-time algorithm for computing a tree representation.
机译:集合族是整个宇宙中集合的集合。如果一个集合族满足某些封闭属性,那么它就可以通过标记的树来有效表示其成员。树的大小与宇宙的大小成正比,而固定家庭成员的数量可以是指数级的。计算这样的有效表示是算法设计中的重要任务。通常不显式地给出集合族(通过列出其成员),而是隐式表示。我们考虑有效地计算集合族的树表示的问题。假设存在用于解决隶属关系和分离问题的有效算法,我们证明如果集合族满足弱闭合特性,那么就存在一种用于计算集合族的树表示的有效算法。对于两个基本问题,算法的运行时间将主要取决于算法的运行时间。我们的算法归纳了先前的几个结果,并为大类图的分解提供了统一的计算方法。我们还为有向图引入了没有无向类似物的分解概念。我们证明本文第一部分的结果适用于这种新的分解。最后,给出了针对这两个基本问题的有效算法,并获得了用于计算树表示的σ(n〜3)-时间算法。

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