Generalized Stable Matching in Bipartite Networks

Mathematics – Optimization and Control

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

In this paper we study the generalized version of weighted matching in bipartite networks. Consider a weighted matching in a bipartite network in which the nodes derive value from the split of the matching edge assigned to them if they are matched. The value a node derives from the split depends both on the split as well as the partner the node is matched to. We assume that the value of a split to the node is continuous and strictly increasing in the part of the split assigned to the node. A stable weighted matching is a matching and splits on the edges in the matching such that no two adjacent nodes in the network can split the edge between them so that both of them can derive a higher value than in the matching. We extend the weighted matching problem to this general case and study the existence of a stable weighted matching. We also present an algorithm that converges to a stable weighted matching. The algorithm generalizes the Hungarian algorithm for bipartite matching. Faster algorithms can be made when there is more structure on the value functions.

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

Generalized Stable Matching in Bipartite Networks 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 Generalized Stable Matching in Bipartite Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Generalized Stable Matching in Bipartite Networks will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-444965

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