Learn to Relax: Integrating 0-1 Integer Linear Programming with Pseudo-Boolean Conflict-Driven Search

accepted for publication
  • Conflict-driven pseudo-Boolean solvers optimize 0-1 integer linear programs by extending the conflict-driven clause learning (CDCL) paradigm from SAT solving. Though pseudo-Boolean solvers have the potential to be exponentially more efficient than CDCL solvers in theory, in practice they can sometimes get hopelessly stuck even when the linear programming (LP) relaxation is infeasible over the reals. Inspired by mixed integer programming (MIP), we address this problem by interleaving incremental LP solving with cut generation within the conflict-driven pseudo-Boolean search. This hybrid approach, which for the first time combines MIP techniques with full-blown conflict analysis operating directly on linear inequalities using the cutting planes method, significantly improves performance on a wide range of benchmarks, approaching a "best-of-both-worlds" scenario between SAT-style conflict-driven search and MIP-style branch-and-cut.

Export metadata

Additional Services

Share in Twitter Search Google Scholar
Author:Ambros Gleixner, Jakob Nordström, Jo Devriendt
Document Type:Article
Parent Title (English):Constraints
Year of first publication:2020