In this paper, we propose a general class of linear programs that admit efficient parallel approximations and use it for efficient parallel approximations to hard combinatorial optimization problems. © Springer-Verlag Berlin Heidelberg 2000.
CITATION STYLE
Efraimidis, P. S., & Spirakis, P. G. (2000). Positive linear programming extensions: Parallel complexity and applications. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1900, 456–460. https://doi.org/10.1007/3-540-44520-x_60
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