We consider the feedback vertex set problem in undirected graphs (FVS). The input to FVS is an undirected graph $G=(V,E)$ with non-negative vertex costs. The goal is to find a least cost subset of vertices $S \subseteq V$ such that $G-S$ is acyclic. FVS is a well-known NP-hard problem with no $(2-\epsilon)$-approximation assuming the Unique Games Conjecture and it admits a $2$-approximation via combinatorial local-ratio methods (Bafna, Berman and Fujito, Algorithms and Computations '95; Becker and Geiger, Artificial Intelligence '96) which can also be interpreted as LP-based primal-dual algorithms (Chudak, Goemans, Hochbaum and Williamson, Operations Research Letters '98). Despite the existence of these algorithms for several decades, there is no known polynomial-time solvable LP relaxation for FVS with a provable integrality gap of at most $2$. More recent work (Chekuri and Madan SODA '16) developed a polynomial-sized LP relaxation for a more general problem, namely Subset FVS, and showed that its integrality gap is at most $13$ for Subset FVS, and hence also for FVS. Motivated by this gap in our knowledge, we undertake a polyhedral study of FVS and related problems. In this work, we formulate new integer linear programs (ILPs) for FVS whose LP-relaxation can be solved in polynomial time, and whose integrality gap is at most $2$. The new insights in this process also enable us to prove that the formulation in (Chekuri and Madan, SODA '16) has an integrality gap of at most $2$ for FVS. Our results for FVS are inspired by new formulations and polyhedral results for the closely-related pseudoforest deletion set problem (PFDS). Our formulations for PFDS are in turn inspired by a connection to the densest subgraph problem. We also conjecture an extreme point property for a LP-relaxation for FVS, and give evidence for the conjecture via a corresponding result for PFDS.
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我们考虑无向图中的反馈顶点集问题(FVS)。输入为具有非负顶点成本的无向图$G(V,E)$。目标是找到一个最少的成本顶点子集$S \subseteq V$,使$G-S$是无环的。FVS是一个众所周知的NP难问题,假设唯一游戏猜想(Unique Games Conjecture)没有$(2-\epsilon)$-逼近,并且通过组合局部比率方法(Bafna,Berman和Fujito,算法和计算'95; Becker 和Geiger,人工智能'96)可以获得2近似度,这也可以被解释为基于LP的原始-对偶算法(Chudak,Goemans,Hochbaum和Williamson,运筹学信件'98)。尽管存在这些算法已有几十年之久,但尚无已知的FVS具有证明性整数不可分性差距不超过2的多项式时间可解线性规划松弛。最近的工作(Chekuri and Madan SODA'16)为更一般的问题Subset FVS开发了一个多项式大小的线性规划松弛,并证明其整数间隙最多为13,因此也为FVS。受到我们的FVS中的这一知识空缺的启发,我们进行了FVS和相关问题的多面体研究。在这项工作中,我们为FVS制定了新的整数线性规划(ILP),它们的线性规划松弛可以在多项式时间内解决,其整数性差距最多为2。这个过程中的新见解也使我们证明了(Chekuri and Madan,SODA'16)中的公式对于FVS至多具有2的整数差距。我们针对FVS的结果受到与之密切相关的伪森林删除集问题(PFDS)的新表述和多面体结果的启发。我们对于PFDS的公式也受到连接到最密子图问题的影响。我们还推测了关于FVS线性规划松弛的极端点性质,并通过PFDS的相应结果为推测提供了证据。