Oblivious Algorithms for the Maximum Directed Cut Problem

Computer Science – Data Structures and Algorithms

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

This paper introduces a special family of randomized algorithms for Max DICUT that we call oblivious algorithms. Let the bias of a vertex be the ratio between the total weight of its outgoing edges and the total weight of all its edges. An oblivious algorithm selects at random in which side of the cut to place a vertex v, with probability that only depends on the bias of v, independently of other vertices. The reader may observe that the algorithm that ignores the bias and chooses each side with probability 1/2 has an approximation ratio of 1/4, whereas no oblivious algorithm can have an approximation ratio better than 1/2 (with an even directed cycle serving as a negative example). We attempt to characterize the best approximation ratio achievable by oblivious algorithms, and present results that are nearly tight. The paper also discusses natural extensions of the notion of oblivious algorithms, and extensions to the more general problem of Max 2-AND.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Oblivious Algorithms for the Maximum Directed Cut Problem does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Oblivious Algorithms for the Maximum Directed Cut Problem, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Oblivious Algorithms for the Maximum Directed Cut Problem will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-512371

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.