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Adaptive Use of Iterative Methods in Predictor-Corrector Interior Point Methods for Linear Programming

dc.contributor.authorWang, Weichungen_US
dc.contributor.authorO'Leary, Dianne P.en_US
dc.description.abstractIn this work we devise efficient algorithms for finding the search directions for interior point methods applied to linear programming problems. There are two innovations. The first is the use of updating of preconditioners computed for previous barrier parameters. The second is an adaptive automated procedure for determining whether to use a direct or iterative solver, whether to reinitialize or update the preconditioner, and how many updates to apply. These decisions are based on predictions of the cost of using the different solvers to determine the next search direction, given costs in determining earlier directions. We summarize earlier results using a modified version of the OB1-R code of Lustig, Marsten, and Shanno, and we present results from a predictor-corrector code PCx modified to use adaptive iteration. If a direct method is appropriate for the problem, then our procedure chooses it, but when an iterative procedure is helpful, substantial gains in efficiency can be obtained. (Also cross-referenced as UMIACS-TR-99-21)en_US
dc.format.extent243841 bytes
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-4011en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-99-21en_US
dc.titleAdaptive Use of Iterative Methods in Predictor-Corrector Interior Point Methods for Linear Programmingen_US
dc.typeTechnical Reporten_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US

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