Convex normalizations in lift-and-project methods for 0-1 programming
Branch-and-Cut algorithms for general 0-1 mixed integer programs can be successfully implemented by using Lift-and-Project (L&P) methods to generate cuts. L&P cuts are drawn from a cone of valid inequalities that is unbounded and, thus, needs to be truncated, or "normalized". We co...
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| Veröffentlicht in: | Annals of operations research 2002-10, Vol.116 (1), p.91 |
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| creator | Rey, Pablo A Sagastizabal, Claudia A |
| description | Branch-and-Cut algorithms for general 0-1 mixed integer programs can be successfully implemented by using Lift-and-Project (L&P) methods to generate cuts. L&P cuts are drawn from a cone of valid inequalities that is unbounded and, thus, needs to be truncated, or "normalized". We consider general normalizations defined by arbitrary closed convex sets and derive dual problems for generating L&P cuts. This unified theoretical framework generalizes and covers a wide group of already known normalizations. We also give conditions for proving finite convergence of the cutting plane procedure that results from using such general L&P cuts. [PUBLICATION ABSTRACT] |
| doi_str_mv | 10.1023/A:1021320028145 |
| format | Article |
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| subjects | Algorithms Computer programming Convex analysis Integer programming Linear programming Operations research Studies |
| title | Convex normalizations in lift-and-project methods for 0-1 programming |
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