Lower Bound for the Number of Iterations in Semidefinite Hierarchies for the Cut Polytope

نویسنده

  • Monique Laurent
چکیده

1.1. Preamble. Given a graph G = V E and a subset A ⊆ V , the cut determined by A is the vector A ∈ ±1 E with ijth entry −1 if and only if A∩ i j = 1. The cut polytope CUT G is the polytope in E defined as the convex hull of all cuts A (A⊆ V ). Given edge weights w ∈ E , the max-cut problem is the problem of finding a cut A whose weight ∑ ij∈E i∈A j ∈A wij is maximum. Hence, it can be formulated as the linear programming problem:

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Tighter Linear and Semidefinite Relaxations for Max-cut Based on the Lovász–schrijver Lift-and-project Procedure∗

We study how the lift-and-project method introduced by Lovász and Schrijver [SIAM J. Optim., 1 (1991), pp. 166–190] applies to the cut polytope. We show that the cut polytope of a graph can be found in k iterations if there exist k edges whose contraction produces a graph with no K5-minor. Therefore, for a graph G with n ≥ 4 nodes with stability number α(G), n − 4 iterations suffice instead of ...

متن کامل

Exponential lower bounds on fixed-size psd rank and semidefinite extension complexity

There has been a lot of interest recently in proving lower bounds on the size of linear programs needed to represent a given polytope P . In a breakthrough paper Fiorini et al. [FMP12] showed that any linear programming formulation of maximum-cut must have exponential size. A natural question to ask is whether one can prove such strong lower bounds for semidefinite programming formulations. In ...

متن کامل

LP and SDP branch-and-cut algorithms for the minimum graph bisection problem: a computational comparison

While semidefinite relaxations are known to deliver good approximations for combinatorial optimization problems like graph bisection, their practical scope is mostly associated with small dense instances. For large sparse instances, cutting plane techniques are considered the method of choice. These are also applicable for semidefinite relaxations via the spectral bundle method, which allows to...

متن کامل

Polytopes of Minimum Positive Semidefinite Rank

The positive semidefinite (psd) rank of a polytope is the smallest k for which the cone of k × k real symmetric psd matrices admits an affine slice that projects onto the polytope. In this paper we show that the psd rank of a polytope is at least the dimension of the polytope plus one, and we characterize those polytopes whose psd rank equals this lower bound.

متن کامل

An Interior Point Algorithm for Solving Convex Quadratic Semidefinite Optimization Problems Using a New Kernel Function

In this paper, we consider convex quadratic semidefinite optimization problems and provide a primal-dual Interior Point Method (IPM) based on a new kernel function with a trigonometric barrier term. Iteration complexity of the algorithm is analyzed using some easy to check and mild conditions. Although our proposed kernel function is neither a Self-Regular (SR) fun...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Math. Oper. Res.

دوره 28  شماره 

صفحات  -

تاریخ انتشار 2003