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dc.contributor.authorPinar Mustafa, C.en_US
dc.contributor.authorZenios Stavros, A.en_US
dc.date.accessioned2016-02-08T10:52:38Z
dc.date.available2016-02-08T10:52:38Z
dc.date.issued1994en_US
dc.identifier.issn983500en_US
dc.identifier.urihttp://hdl.handle.net/11693/25934
dc.description.abstractWe describe the development of a data-level, massively parallel software system for the solution of multicommodity network flow problems. Using a smooth linear-quadratic penalty (LQP) algorithm we transform the multicommodity network flow problem into a sequence of independent min-cost network flow subproblems. The solution of these problems is coordinated via a simple, dense, nonlinear master program to obtain a solution that is feasible within some user-specified tolerance to the original multicommodity network flow problem. Particular emphasis is placed on the mapping of both the subproblem and master problem data to the processing elements of a massively parallel computer, the Connection Machine CM-2. As a result of this design we can solve large and sparse optimization problems on current SIMD massively parallel architectures. Details of the implementation are reported, together with summary computational results with a set of test problems drawn from a Military Airlift Command application.en_US
dc.language.isoEnglishen_US
dc.source.titleACM Transactions on Mathematical Softwareen_US
dc.relation.isversionofhttp://dx.doi.org/10.1145/198429.198439en_US
dc.subjectComputer architectureen_US
dc.subjectComputer systems programmingen_US
dc.subjectConstraint theoryen_US
dc.subjectMathematical programmingen_US
dc.subjectOptimizationen_US
dc.subjectParallel algorithmsen_US
dc.subjectParallel processing systemsen_US
dc.subjectMulticommodity network problemsen_US
dc.subjectParallel linear quadratic penalty algorithmen_US
dc.subjectParallel optimizationen_US
dc.subjectAlgorithmsen_US
dc.titleData-level parallel linear-quadratic penalty algorithm for multicommodity network flowsen_US
dc.typeResearch Paperen_US
dc.departmentBilkent Universityen_US
dc.citation.spage531en_US
dc.citation.epage552en_US
dc.citation.volumeNumber20en_US
dc.citation.issueNumber4en_US
dc.identifier.doi10.1145/198429.198439en_US
dc.publisherACM, New York, NY, United Statesen_US


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