When LP is the cure for your matching woes: Improved bounds for stochastic matchings (Extended abstract)

N. Bansal, A. Gupta, J. Liu, J. Mestre, V. Nagarajan, A. Rudra

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    19 Citations (Scopus)
    1 Downloads (Pure)

    Abstract

    Consider a random graph model where each possible edge e is present independently with some probability p_e . We are given these numbers p_e , and want to build a large/heavy matching in the randomly generated graph. However, the only way we can find out whether an edge is present or not is to query it, and if the edge is indeed present in the graph, we are forced to add it to our matching. Further, each vertex i is allowed to be queried at most t_i times. How should we adaptively query the edges to maximize the expected weight of the matching? We consider several matching problems in this general framework (some of which arise in kidney exchanges and online dating, and others arise in modeling online advertisements); we give LP-rounding based constant-factor approximation algorithms for these problems. Our main results are: * We give a 5.75-approximation for weighted stochastic matching on general graphs, and a 5-approximation on bipartite graphs. This answers an open question from [Chen et al. ICALP 09]. * Combining our LP-rounding algorithm with the natural greedy algorithm, we give an improved 3.88-approximation for unweighted stochastic matching on general graphs and 3.51-approximation on bipartite graphs. * We introduce a generalization of the stochastic online matching problem [Feldman et al. FOCS 09] that also models preference-uncertainty and timeouts of buyers, and give a constant factor approximation algorithm.
    Original languageEnglish
    Title of host publicationAlgorithms - ESA 2010 (18th Annual European Symposium, Liverpool, UK, September 6-8, 2010. Proceedings, Part II)
    EditorsM. Berg, de, U. Meyer
    Place of PublicationBerlin
    PublisherSpringer
    Pages218-229
    ISBN (Print)978-3-642-15780-6
    DOIs
    Publication statusPublished - 2010

    Publication series

    NameLecture Notes in Computer Science
    Volume6346
    ISSN (Print)0302-9743

    Fingerprint Dive into the research topics of 'When LP is the cure for your matching woes: Improved bounds for stochastic matchings (Extended abstract)'. Together they form a unique fingerprint.

    Cite this