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Submodular maximization and its generalization through an intersection cut lens

  • Liding Xu,
  • Leo Liberti

摘要

We study a mixed-integer set \(\mathcal {S}:=\{(x,t) \in \{0,1\}^n \times \mathbb {R}: f(x) \ge t\}\) S : = { ( x , t ) { 0 , 1 } n × R : f ( x ) t } arising in the submodular maximization problem, where f is a submodular function defined over \(\{0,1\}^n\) { 0 , 1 } n . We use intersection cuts to tighten a polyhedral outer approximation of \(\mathcal {S}\) S . We construct a continuous extension \(\bar{\textsf{F}}_f\) F ¯ f of f, which is convex and defined over the entire space \(\mathbb {R}^n\) R n . We show that the epigraph \({{\,\textrm{epi}\,}}(\bar{\textsf{F}}_f)\) epi ( F ¯ f ) of \(\bar{\textsf{F}}_f\) F ¯ f is an \(\mathcal {S}\) S -free set, and characterize maximal \(\mathcal {S}\) S -free sets containing \({{\,\textrm{epi}\,}}(\bar{\textsf{F}}_f)\) epi ( F ¯ f ) . We propose a hybrid discrete Newton algorithm to compute an intersection cut efficiently and exactly. Our results are generalized to the hypograph or the superlevel set of a submodular-supermodular function over the Boolean hypercube, which is a model for discrete nonconvexity. A consequence of these results is intersection cuts for Boolean multilinear constraints. We evaluate our techniques on max cut, pseudo Boolean maximization, and Bayesian D-optimal design problems within a MIP solver.