Abstract
The relaxation algorithm for linear programming is revised in this paper. Based on cluster structure, a parallel revised algorithm is presented. Its performance is analyzed. The experimental results on DAWNING 3000 are also given. Theoretical analysis and experimental results show that the revised relaxation algorithm improves the performance of the relaxation algorithm, and it has good parallelism and is very robust. Therefore, it can expect to be applied to the solution of the large-scale linear programming problems rising from practical application. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Zhang, J., Li, Q., Song, Y., & Qu, Y. (2006). A new efficient parallel revised relaxation algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4113 LNCS-I, pp. 812–821). Springer Verlag. https://doi.org/10.1007/11816157_98
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