Özaktaş, HakanAkgül, MustafaPınar, Mustafa Ç.2016-02-082016-02-0819960302-9743http://hdl.handle.net/11693/27750Date of Conference: 18-21 August 1996Conference Name: 3rd International Workshop on Applied Parallel Computing, PARA 1996The linear feasibility problem arises in several areas of applied mathematics and medical science, in several forms of image reconstruction problems. The surrogate constraint algorithm of Yang and Murty for the linear feasibility problem is implemented and analyzed. The sequential approach considers projections one at a time. In the parallel approach, several projections are made simultaneously and their convex combination is taken to be used at the next iteration. The sequential method is compared with the parallel method for varied numbers of processors. Two improvement schemes for the parallel method are proposed and tested.EnglishDistributed computingLinear and convex feasibilityParallel algorithmsProjection methodsImage reconstructionMedical imagingMedical problemsOptimizationApplied mathematicsConvex combinationsConvex feasibilityFeasibility problemSequential approachSurrogate constraintsIterative methodsConference Paper10.1007/3-540-62095-8_61