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Runtimes on highly sparse, random LPs with varying numbers of constraints.

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posted on 20.02.2013, 00:18 by Oliver Serang

The simplex and affine-scaling algorithms were timed against the conic sampling algorithm on random LP problems with n = 100, with 95% sparsity, and with number of constraints k = 128,…,16384. For each k, three problems were generated and timed with all algorithms. Error bars indicate minimum and maximum runtimes. Fully sparse vector data structures were used.

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