论文标题
在对称破坏不平等的几何形状上
On the geometry of symmetry breaking inequalities
论文作者
论文摘要
打破对称性是对对称整数程序的分支和结合方法的流行方式。我们研究基本域,这些结构域是最小和封闭的对称性破坏多面体的。我们的长期目标是了解这种多面体的复杂性与它们对称性破坏能力之间的关系。 从几何群体理论中借用思想,我们提供了将群体的作用与基本领域的几何形状相关联的结构属性。受这些见解的启发,我们为基本领域提供了新的广义构造,我们称之为广义的dirichlet域(GDD)。我们的构造是递归的,并利用了在$ \ mathbb {r}^n $中修复给定向量的子组的固定分解。我们使用这种结构来分析Salvagnin(2018)以及Liberti和Ostrowski(2014)的最近引入的对称破坏不平等,称为Schreier-SIMS不平等现象。特别是,这表明每个排列组都承认一个基本域,其面积不到$ n $。我们还表明,这种界限很紧。 最后,我们证明Schreier-SIM不平等可能包含给定置换式$ g $的同构二进制矢量的指数数量,这提供了该基本域缺乏对称性破坏效率的证据。相反,适合此$ G $的适当构建的GDD线性许多不平等,并包含异构二进制矢量的独特代表。
Breaking symmetries is a popular way of speeding up the branch-and-bound method for symmetric integer programs. We study fundamental domains, which are minimal and closed symmetry breaking polyhedra. Our long-term goal is to understand the relationship between the complexity of such polyhedra and their symmetry breaking capability. Borrowing ideas from geometric group theory, we provide structural properties that relate the action of the group with the geometry of the facets of fundamental domains. Inspired by these insights, we provide a new generalized construction for fundamental domains, which we call generalized Dirichlet domain (GDD). Our construction is recursive and exploits the coset decomposition of the subgroups that fix given vectors in $\mathbb{R}^n$. We use this construction to analyze a recently introduced set of symmetry breaking inequalities by Salvagnin (2018) and Liberti and Ostrowski (2014), called Schreier-Sims inequalities. In particular, this shows that every permutation group admits a fundamental domain with less than $n$ facets. We also show that this bound is tight. Finally, we prove that the Schreier-Sims inequalities can contain an exponential number of isomorphic binary vectors for a given permutation group $G$, which provides evidence of the lack of symmetry breaking effectiveness of this fundamental domain. Conversely, a suitably constructed GDD for this $G$ has linearly many inequalities and contains unique representatives for isomorphic binary vectors.