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Rank bounds for a hierarchy of Lovász and Schrijver

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  • Pratik Worah

    (Courant Institute of Mathematical Sciences)

Abstract

Lovász and Schrijver introduced several lift and project methods for 0–1 integer programs, now collectively known as Lovász–Schrijver (LS) hierarchies. Several lower bounds have since been proven for the rank of various linear programming relaxations in the LS and $$\hbox {LS}_+$$ LS + hierarchies. We investigate rank bounds in the more general $$\hbox {LS}_*$$ LS ∗ hierarchy, which allows lifts by any derived inequality as opposed to just $$x\ge 0$$ x ≥ 0 and $$1-x\ge 0$$ 1 - x ≥ 0 in the LS hierarchy. Rank lower bounds for $$\hbox {LS}_*$$ LS ∗ were obtained for the symmetric knapsack polytope by Grigoriev et al. We reinitiate further investigation into such general lifts. We prove simple upper bounds on rank which show that under such general lifts one can potentially converge to the integer solution much faster than $$\hbox {LS}_+$$ LS + or Sherali–Adams (SA) hierarchy. This motivates our investigation of rank lower bounds and integrality gaps for $$\hbox {LS}_*$$ LS ∗ and the $$\hbox {SA}_*$$ SA ∗ hierarchy, the latter is a generalization of the SA hierarchy in the same vein as $$\hbox {LS}_*$$ LS ∗ . In particular, we show that the $$\hbox {LS}_*$$ LS ∗ rank of $$PHP_n^{n+1}$$ P H P n n + 1 is $$\sim \log _2n$$ ∼ log 2 n . We also extend the rank lower bounds and integrality gaps for SA hierarchy to the $$\hbox {LS}_*$$ LS ∗ and $$\hbox {SA}_*$$ SA ∗ hierarchies as long as the maximum number of variables in any constraint of the initial linear program is bounded by a constant.

Suggested Citation

  • Pratik Worah, 2015. "Rank bounds for a hierarchy of Lovász and Schrijver," Journal of Combinatorial Optimization, Springer, vol. 30(3), pages 689-709, October.
  • Handle: RePEc:spr:jcomop:v:30:y:2015:i:3:d:10.1007_s10878-013-9662-4
    DOI: 10.1007/s10878-013-9662-4
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    References listed on IDEAS

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    1. Hanif D. Sherali & Warren P. Adams & Patrick J. Driscoll, 1998. "Exploiting Special Structures in Constructing a Hierarchy of Relaxations for 0-1 Mixed Integer Problems," Operations Research, INFORMS, vol. 46(3), pages 396-405, June.
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    3. Monique Laurent, 2003. "A Comparison of the Sherali-Adams, Lovász-Schrijver, and Lasserre Relaxations for 0--1 Programming," Mathematics of Operations Research, INFORMS, vol. 28(3), pages 470-496, August.
    4. Michel X. Goemans & Levent Tunçel, 2001. "When Does the Positive Semidefiniteness Constraint Help in Lifting Procedures?," Mathematics of Operations Research, INFORMS, vol. 26(4), pages 796-815, November.
    5. Kevin K. H. Cheung, 2007. "Computation of the Lasserre Ranks of Some Polytopes," Mathematics of Operations Research, INFORMS, vol. 32(1), pages 88-94, February.
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    Cited by:

    1. Adam Kurpisz & Samuli Leppänen & Monaldo Mastrolilli, 2018. "Sum-of-squares rank upper bounds for matching problems," Journal of Combinatorial Optimization, Springer, vol. 36(3), pages 831-844, October.

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