Article ID Journal Published Year Pages File Type
1141706 Discrete Optimization 2008 13 Pages PDF
Abstract

We study the problem of optimizing nonlinear objective functions over bipartite matchings. While the problem is generally intractable, we provide several efficient algorithms for it, including a deterministic algorithm for maximizing convex objectives, approximative algorithms for norm minimization and maximization, and a randomized algorithm for optimizing arbitrary objectives.

Related Topics
Physical Sciences and Engineering Mathematics Control and Optimization
Authors
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