Feature Article—Interior Point Methods for Linear Programming: Computational State of the Art | Zendy

Irvin J. Lustig | Zendy; Roy E. Marsten | Zendy; David F. Shanno | Zendy

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Feature Article—Interior Point Methods for Linear Programming: Computational State of the Art

Author(s) -

Irvin J. Lustig,

Roy E. Marsten,

David F. Shanno

Publication year - 1994

Publication title -

informs journal on computing

Language(s) - English

Resource type - Journals

eISSN - 2326-3245

pISSN - 0899-1499

DOI - 10.1287/ijoc.6.1.1

Subject(s) - interior point method , simplex , linear programming , computer science , code (set theory) , preprocessor , simplex algorithm , state (computer science) , matrix (chemical analysis) , field (mathematics) , algorithm , mathematical optimization , mathematics , programming language , combinatorics , pure mathematics , materials science , set (abstract data type) , composite material

A survey of the significant developments in the field of interior point methods for linear programming is presented, beginning with Karmarkar's projective algorithm and concentrating on the many variants that can be derived from logarithmic barrier methods. Full implementation details of the primal-dual predictor-corrector code OB1 are given, including preprocessing, matrix orderings, and matrix factorization techniques. A computational comparison of OB1 with a state-of-the-art simplex code using eight large models is given. In addition, computational results are presented where OB1 is used to solve two very large models that have never been solved by any simplex code INFORMS Journal on Computing , ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.

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