On Set Expansion Problems And The Small Set Expansion Conjecture

We study two problems related to the Small Set Expansion Conjecture [14]: the Maximum weight m'-edge cover (MWEC) problem and the Fixed cost minimum edge cover (FCEC) problem. In the MWEC problem, we are given an undirected simple graph G = (V, E) with integral vertex weights. The goal is to select a set U subset of V of maximum weight so that the number of edges with at least one endpoint in U is at most Goldschmidt and Hochbaum [8] show that the problem is NP-hard and they give a 3-approximation algorithm for the problem. The approximation guarantee was improved to 2 + epsilon, for any fixed epsilon > 0 [1 2]. We present an approximation algorithm that achieves a guarantee of 2. Interestingly, we also show that for any constant E > 0, a (2 6) ratio for MWEC implies that the Small Set Expansion Conjecture [14] does not hold. Thus, assuming the Small Set Expansion Conjecture, the bound of 2 is tight. In the FCEC problem, we are given a vertex weighted graph, a bound k, and our goal is to find a subset of vertices U of total weight at least k such that the number of edges with at least one edges in U is minimized. A 2(1 + epsilon)-approximation for the problem follows from the work of Carnes and Shmoys [3]. We improve the approximation ratio by giving a 2-approximation algorithm for the problem and show a (2 - epsilon)-inapproximability under Small Set Expansion Conjecture conjecture. Only the NP-hardness result was known for this problem [8]. We show that a natural linear program for FCEC has an integrality gap of 2 o(1). We also show that for any constant p > 1, an approximation guarantee of p for the FCEC problem implies a p(1+ o(1)) approximation for MWEC. Finally, we define the Degrees density augmentation problem which is the density version of the FCEC problem. In this problem we are given an undirected graph G = (V, E) and a set U C V. The objective is to find a set W so that (e(W) e(U,W))I deg(W) is maximum. This problem admits an LP-based exact solution ['1]. We give a combinatorial algorithm for this problem.