An Efficient Approximation Algorithm for Max-Cut
نویسندگان
چکیده
منابع مشابه
An Efficient Approximation Algorithm for Max-Cut
Significant research effort has been devoted in the study of approximation algorithms for NP-hard problems. Ap-proximation algorithm for Max-Cut problem with performance guarantee of 0. 87856 is long known. In this work we study balanced Max-Cut problem. We give a balancing factor ? for given ? such that the approximate solution is at least 0. 87856 times the optimal ?-balanced cut and it is it...
متن کاملApproximation Algorithm for the Max-Cut Problem
In this project, we investigated several approximation algorithms for the Max-Cut problem. Our main approach to this problem is a semideenite program (GW) based algorithm that has a performance guarantee of at least 0.878 of the optimal cut. We also show that we can perform exhaustive local search on top of the GW to enhance the result. Our results show that the running time of the local search...
متن کاملLecture 17: Approximation algorithm for max-cut
Given an undirected graph G = (V,E), the max-cut problem asks for the partition S1, S2 ⊆ V , s.t., the number of edges going from S1 to S2 are maximized. Remember that since S1, S2 is a partition, so S1∪S2 = V and S1 ∩ S2 = ∅. Clearly this is an optimization problem. It is known to be NP-hard and so not expected to have a polynomial time algorithm. We are interested in finding an approximation ...
متن کاملNear-optimal approximation algorithm for simultaneous Max-Cut
In the simultaneous Max-Cut problem, we are given k weighted graphs on the same set of n vertices, and the goal is to find a cut of the vertex set so that the minimum, over the k graphs, of the cut value is as large as possible. Previous work [BKS15] gave a polynomial time algorithm which achieved an approximation factor of 1{2 ́ op1q for this problem (and an approximation factor of 1{2 ` εk in...
متن کاملRandomized Approximation of MAX-CUT
1 Last Class In the previous class we discussed averaging arguments, derandomization, the method of conditional expectation, and looked at the general technique of relaxation and randomized rounding with respect to MAX-SAT. To solve (approximate) MAX-SAT, we relaxed the requirement that the variables be boolean and instead let them take on real values in the interval 0; 1]. We then solved the r...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2013
ISSN: 0975-8887
DOI: 10.5120/10484-5234