Abstract
The 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.
The authors are indebted to K. Madsen for providing financial support to this project.
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© 1996 Springer-Verlag Berlin Heidelberg
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Özaktaş, H., Akgül, M., Pinar, M.Ç. (1996). The parallel surrogate constraint approach to the linear feasibility problem. In: Waśniewski, J., Dongarra, J., Madsen, K., Olesen, D. (eds) Applied Parallel Computing Industrial Computation and Optimization. PARA 1996. Lecture Notes in Computer Science, vol 1184. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62095-8_61
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DOI: https://doi.org/10.1007/3-540-62095-8_61
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