Learn to relax : Integrating 0-1 integer linear programming with pseudo-Boolean conflict-driven search
(2021) In Constraints 26(44565). p.26-55- 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... (More)
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.
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- author
- Devriendt, Jo LU ; Gleixner, Ambros and Nordström, Jakob LU
- organization
- publishing date
- 2021-01-18
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Conflict-driven search, Cut generation, Cutting plane proofs, Integer Programming, Linear Programming, Pseudo-Boolean, RoundingSat
- in
- Constraints
- volume
- 26
- issue
- 44565
- pages
- 26 - 55
- publisher
- Springer
- external identifiers
-
- scopus:85100195550
- ISSN
- 1383-7133
- DOI
- 10.1007/s10601-020-09318-x
- language
- English
- LU publication?
- yes
- id
- e4218a40-cead-45f7-a954-9fa54c847136
- date added to LUP
- 2021-02-12 12:58:37
- date last changed
- 2022-05-12 18:19:34
@article{e4218a40-cead-45f7-a954-9fa54c847136, abstract = {{<p>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.</p>}}, author = {{Devriendt, Jo and Gleixner, Ambros and Nordström, Jakob}}, issn = {{1383-7133}}, keywords = {{Conflict-driven search; Cut generation; Cutting plane proofs; Integer Programming; Linear Programming; Pseudo-Boolean; RoundingSat}}, language = {{eng}}, month = {{01}}, number = {{44565}}, pages = {{26--55}}, publisher = {{Springer}}, series = {{Constraints}}, title = {{Learn to relax : Integrating 0-1 integer linear programming with pseudo-Boolean conflict-driven search}}, url = {{http://dx.doi.org/10.1007/s10601-020-09318-x}}, doi = {{10.1007/s10601-020-09318-x}}, volume = {{26}}, year = {{2021}}, }