Nonpolyhedral Relaxations of Graph-Bisection Problems
نویسندگان
چکیده
We study the problem of nding the minimum bisection of a graph into two parts of prescribed sizes. We formulate two lower bounds on the problem by relaxing nodeand edgeincidence vectors of cuts. We prove that both relaxations provide the same bound. The main fact we prove is that the duality between the relaxed edgeand nodevectors preserves very natural cardinality constraints on cuts. We present an analogous result also for the max-cut problem, and show a relation between the edge relaxation and some other optimality criteria studied before. Finally, we brie y mention possible applications for a practical computational approach.
منابع مشابه
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 کاملAn Interior-point Method for Semideenite Programming
We propose a new interior point based method to minimize a linear function of a matrix variable subject to linear equality and inequality constraints over the set of positive semideenite matrices. We show that the approach is very eecient for graph bisection problems, such as max-cut. Other applications include max-min eigenvalue problems and relaxations for the stable set problem.
متن کامل1 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 کاملAn Interior-Point Method for Semidefinite Programming
We propose a new interior point based method to minimize a linear function of a matrix variable subject to linear equality and inequality constraints over the set of positive semidefinite matrices. We show that the approach is very efficient for graph bisection problems, such as max-cut. Other applications include max-min eigenvalue problems and relaxations for the stable set problem.
متن کاملCoping with Np-hardness: Approximating Minimum Bisection and Heuristics for Maximum Clique 2 Approximating Minimum Bisection 13 1.2 Approximation Algorithms
Many important optimization problems are known to be NP-hard. That is, unless P = NP, there is no polynomial time algorithm that optimally solves these problems on every input instance. We study algorithmic ways for \coping" with NP-hard optimization problems. One possible approach for coping with the NP-hardness is to relax the requirement for exact solution, and devise approximation algorithm...
متن کاملذخیره 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 ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- SIAM Journal on Optimization
دوره 5 شماره
صفحات -
تاریخ انتشار 1995