On Constrained Mixed-Integer DR-Submodular Minimization

Author:

Yu Qimeng1ORCID,Küçükyavuz Simge2ORCID

Affiliation:

1. Département d’Informatique et de Recherche Opérationnelle, Université de Montréal, Montréal, Quebec H3T 1J4, Canada;

2. Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208

Abstract

Diminishing returns (DR)–submodular functions encompass a broad class of functions that are generally nonconvex and nonconcave. We study the problem of minimizing any DR-submodular function with continuous and general integer variables under box constraints and, possibly, additional monotonicity constraints. We propose valid linear inequalities for the epigraph of any DR-submodular function under the constraints. We further provide the complete convex hull of such an epigraph, which, surprisingly, turns out to be polyhedral. We propose a polynomial-time exact separation algorithm for our proposed valid inequalities with which we first establish the polynomial-time solvability of this class of mixed-integer nonlinear optimization problems. Funding: This work was supported by the Office of Naval Research Global [Grant N00014-22-1-2602].

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

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