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- W3126051750 abstract "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." @default.
- W3126051750 created "2021-02-01" @default.
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- W3126051750 date "2021-01-18" @default.
- W3126051750 modified "2023-10-16" @default.
- W3126051750 title "Learn to relax: Integrating 0-1 integer linear programming with pseudo-Boolean conflict-driven search" @default.
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- W3126051750 doi "https://doi.org/10.1007/s10601-020-09318-x" @default.
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