Box Facets and Cut Facets of Lifted Multicut Polytopes
Lucas Fabian Naumann, Jannik Irmai, Shengxian Zhao, Bjoern Andres
TL;DR
This work analyzes the lifted multicut polytope $\Xi_{G\widehat{G}}$ arising from a graph $G=(V,E)$ and its augmentation $\widehat{G}=(V,E\cup F)$. It provides a necessary, sufficient, and efficiently decidable condition for when a lower box inequality $0 \leq x_{uw}$ defines a facet of $\Xi_{G\widehat{G}}$, using polyhedral arguments and Menger’s theorem. It also proves that deciding facet-definingness for cut inequalities is NP-hard, via a reduction framework including a $f_d$-path construction and a 3-SAT reduction, highlighting intrinsic complexity in the cut-structure of lifted multicut polytopes. Collectively, the results sharpen understanding of the facet structure and have implications for designing effective cutting-plane algorithms for the lifted multicut problem. They also suggest future work on separator-based structures and non-local connectedness to further refine facet characterizations.
Abstract
The lifted multicut problem is a combinatorial optimization problem whose feasible solutions relate one-to-one to the decompositions of a graph $G = (V, E)$. Given an augmentation $\widehat{G} = (V, E \cup F)$ of $G$ and given costs $c \in \mathbb{R}^{E \cup F}$, the objective is to minimize the sum of those $c_{uw}$ with $uw \in E \cup F$ for which $u$ and $w$ are in distinct components. For $F = \emptyset$, the problem specializes to the multicut problem, and for $E = \tbinom{V}{2}$ to the clique partitioning problem. We study a binary linear program formulation of the lifted multicut problem. More specifically, we contribute to the analysis of the associated lifted multicut polytopes: Firstly, we establish a necessary, sufficient and efficiently decidable condition for a lower box inequality to define a facet. Secondly, we show that deciding whether a cut inequality of the binary linear program defines a facet is NP-hard.
