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The steepest descent gravitational method for linear programming
dc.contributor.authorChang, Soo Y. (Soo Young)en_US
dc.contributor.authorMurty, Katta G.en_US
dc.date.accessioned2006-04-07T20:39:34Z
dc.date.available2006-04-07T20:39:34Z
dc.date.issued1989-11en_US
dc.identifier.citationChang, Soo Y., Murty, Katta G. (1989/11)."The steepest descent gravitational method for linear programming." Discrete Applied Mathematics 25(3): 211-239. <http://hdl.handle.net/2027.42/27699>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6TYW-46BHSFH-2/2/4110c84f82d17ea215b42202cd326af5en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/27699
dc.description.abstractWe present a version of the gravitational method for linear programming, based on steepest descent gravitational directions. Finding the direction involves a special small "nearest point problem" that we solve using an efficient geometric approach. The method requires no expensive initialization, and operates only with a small subset of locally active constraints at each step. Redundant constraints are automatically excluded in the main computation. Computational results are provided.en_US
dc.format.extent1975571 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleThe steepest descent gravitational method for linear programmingen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Industrial and Operations Engineering, The University of Michigan, Ann Arbor, MI 48109-2117, USAen_US
dc.contributor.affiliationotherDepartment of Mathematical Sciences, Clemson University, Clemson, SC 29634-1907, USAen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/27699/1/0000085.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0166-218X(89)90002-4en_US
dc.identifier.sourceDiscrete Applied Mathematicsen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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