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Abstract
The proposed algorithm proceeds from dual face to dual face, until reaching a dual optimal face along with a pair of dual and primal optimal solutions, compared with the simplex algorithm, which moves from vertex to vertex. It computes the search direction as an orthogonal projection of the dual objective gradient onto a relevant null space. In each iteration, it solves a single small triangular system, compared with four triangular systems handled by the simplex algorithm. We report preliminary but favorable computational results with a set of standard Netlib test problems.
1. Introduction1.1. The State of the Art.• Simplex algorithm (G. B. Dantzig 1947) • Ellipsoid algorithm ( Khachiyan 1979)• Interior-point algorithm ( Karmarkar 1984) Pan’s work : • The obtuse-angle principle(1990)• Bisection simplex algorithm (1991)• The most-obtuse-angle rules(1997)• Deficient basis & projective pivot algorithms (1997-)• Nested pricing, Largest-distance pricing (2008-) • Affine-scaling pivot algorithm (submitted)
1.2. Basic Idea : Moving from face to face.
1.3. Model.
We are concerned with the linear
programming (LP) problem in the standard form:
The dual problem:
An attractive feature: in each iteration, it solves
a single smaller triangular system.
4.1. More features.
Any expansion iteration must be followed by a contraction
iteration. The latter is called accompanying (contraction)
iteration.
If a component (excluding one that just be set to zero in a
preceding expansion iteration) of is zero, it is termed
degenerate.
5. Phase-1
Auxiliary program:
where
6. Computational results.
DFA: the proposed algorithm.
RSA: dense implementation of the standard revised
simplex algorithm.
Both primal and dual feasibility tolerance were taken to be , and row
relative tolerance was .
Compiled using the Visual FORTRAN 5.0, code DFA and RSA were run
under a Windows XP system Home Edition Version 2002 on an IBM PC
with an Intel(R) Pentium(R) processor 1.00GB of 1.86GHz memory,
and about 16 digits of precision. All reported CPU times were
measured in seconds with utility routine CPU_TIME.
Tested were a set of 26 standard problems from NETLIB.