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Potential-reduction methods in mathematical programming
Todd, Michael J.

Data: 1997
Resum: We provide a survey of interior-point methods for linear programming and its extensions that are based on reducing a suitable potential function at each iteration. We give a fairly complete overview of potential-reduction methods for linear programming, focusing on the possibility of taking long steps and the properties of the barrier function that are necessary for the analysis. We then describe briefly how the methods and results can be extended to certain convex programming problems, following the approach of Nesterov and Todd. We conclude with some open problems.
Drets: Tots els drets reservats
Llengua: Anglès.
Document: article ; recerca ; publishedVersion
Matèria: Linear programming ; Potential functions ; Interior-point methods ; Self-concordant barriers ; Self-scaled barriers
Publicat a: Mathematical Programming, vol. 76 n. 1 (1997) p. 3-45, ISSN 0025-5610

43 p, 2.2 MB
 Accés restringit a la UAB

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