A sparsity-exploiting variant of the Bartels—Golub decomposition for linear programming bases

We describe a sparsity-exploiting variant of the Bartels—Golub decomposition for linear programming bases. It includes interchanges that, whenever this is possible, avoid the use of any eliminations (with consequent fill-ins) when revising the factorization at an iteration. Test results on some medium scale problems are presented and comparisons made with the algorithm of Forrest and Tomlin.

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