Submodular Cost Allocation Problem and Applications

Abstract

We study the Minimum Submodular-Cost Allocation problem (MSCA). In this problem we are given a finite ground set $V$ and $k$ non-negative submodular set functions $f_1,...,f_k$ on $V$. The objective is to partition $V$ into $k$ (possibly empty) sets $A_1,...,A_k$ such that the sum ${\sum }_{i=1}^k{f}_i(A_i)$ is minimized. Several well-studied problems such as the non-metric facility location problem, multiway-cut in graphs and hypergraphs, and uniform metric labeling and its generalizations can be shown to be special cases of MSCA. In this paper we consider a convex-programming relaxation obtained via the Lovász-extension for submodular functions. This allows us to understand several previous relaxations and rounding procedures in a unified fashion and also develop new formulations and approximation algorithms for several problems. In particular, we give a $(1.5-1/k)$-approximation for the hypergraph multiway partition problem. We also give a $\min \{2(1-1/k),H_{\Delta }\}$-approximation for the hypergraph multiway cut problem when $\Delta$ is the maximum hyperedge size. Both problems generalize the multiway cut problem in graphs and the hypergraph cut problem is approximation equivalent to the node-weighted multiway cut problem in graphs.

Extended abstract to appear in Proceedings of ICALP, July 2011

Cited by in corpus (1)

• Approximation Algorithms for Submodular Multiway Partition