Year: 2000
Author: Ping-Qi Pan
Journal of Computational Mathematics, Vol. 18 (2000), Iss. 6 : pp. 587–596
Abstract
In this paper, we propose two new perturbation simplex variants. Solving linear programming problems without introducing artificial variables, each of the two uses the dual pivot rule to achieve primal feasibility, and then the primal pivot rule to achieve optimality. The second algorithm, a modification of the first, is designed to handle highly degenerate problems more efficiently. Some interesting results concerning merit of the perturbation are established. Numerical results from preliminary tests are also reported.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2000-JCM-9069
Journal of Computational Mathematics, Vol. 18 (2000), Iss. 6 : pp. 587–596
Published online: 2000-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 10
Keywords: Linear programming Perturbation Primal simplex algorithm Partially revised tableau.