Advanced Optimization Laboratory Title : A semidefinite programming based polyhedral cut and price approach for the maxcut problem

نویسندگان

  • Kartik Krishnan
  • John Mitchell
  • John E. Mitchell
چکیده

We investigate solution of the maximum cut problem using a polyhedral cut and price approach. The dual of the well-known SDP relaxation of maxcut is formulated as a semi-infinite linear programming problem, which is solved within an interior point cutting plane algorithm in a dual setting; this constitutes the pricing (column generation) phase of the algorithm. Cutting planes based on the polyhedral theory of the maxcut problem are then added to the primal problem in order to improve the SDP relaxation; this is the cutting phase of the algorithm. We provide computational results, and compare these results with a standard SDP cutting plane scheme.

برای دانلود رایگان 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

Title: a Semidefinite Programming Based Polyhedral Cut and Price Approach for the Maxcut Problem a Semidefinite Programming Based Polyhedral Cut and Price Approach for the Maxcut Problem

We investigate solution of the maximum cut problem using a polyhedral cut and price approach. The dual of the well-known SDP relaxation of maxcut is formulated as a semi-infinite linear programming problem, which is solved within an interior point cutting plane algorithm in a dual setting; this constitutes the pricing (column generation) phase of the algorithm. Cutting planes based on the polyh...

متن کامل

A Semidefinite Programming Based Polyhedral Cut and Price Approach for the Maxcut Problem

We investigate solution of the maximum cut problem using a polyhedral cut and price approach. The dual of the well-known SDP relaxation of maxcut is formulated as a semi-infinite linear programming problem, which is solved within an interior point cutting plane algorithm in a dual setting; this constitutes the pricing (column generation) phase of the algorithm. Cutting planes based on the polyh...

متن کامل

1 Parallel Semidefinite Programming and Combinatorial Optimization STEVEN

The use of semidefinite programming in combinatorial optimization continues to grow. This growth can be attributed to at least three factors: new semidefinite relaxations that provide tractable bounds to hard combinatorial problems, algorithmic advances in the solution of semidefinite programs (SDP), and the emergence of parallel computing. Solution techniques for minimizing combinatorial probl...

متن کامل

A Projected Gradient Algorithm for Solving the Maxcut Sdp Relaxation∗

In this paper, we develop a specialized algorithm for solving the semidefinite programming (SDP) relaxation of the maximum cut (maxcut) problem. The maxcut problem has many applications, e.g., in VLSI design and statistical physics (see [2, 4, 5, 19, 21]). Several algorithms have been proposed to find either exact or approximate solutions to this problem. As for many combinatorial optimization ...

متن کامل

Row by row methods for semidefinite programming

We present a row-by-row (RBR) method for solving semidefinite programming (SDP) problem based on solving a sequence of problems obtained by restricting the n-dimensional positive semidefinite constraint on the matrix X. By fixing any (n − 1)-dimensional principal submatrix of X and using its (generalized) Schur complement, the positive semidefinite constraint is reduced to a simple second-order...

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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005