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Mathematical programming via the least-squares method

100%

Übi E.

Open Mathematics

2010

tom 8

nr 4

795-806

The least-squares method is used to obtain a stable algorithm for a system of linear inequalities as well as linear and nonlinear programming. For these problems the solution with minimal norm for a system of linear inequalities is found by solving the non-negative least-squares (NNLS) problem. Approximate and exact solutions of these problems are discussed. Attention is mainly paid to finding the initial solution to an LP problem. For this purpose an NNLS problem is formulated, enabling finding the initial solution to the primal or dual problem, which may turn out to be optimal. The presented methods are primarily suitable for ill-conditioned and degenerate problems, as well as for LP problems for which the initial solution is not known. The algorithms are illustrated using some test problems.

On stable least squares solution to the system of linear inequalities

100%

Übi E.

Open Mathematics

2007

tom 5

nr 2

373-385

The system of inequalities is transformed to the least squares problem on the positive ortant. This problem is solved using orthogonal transformations which are memorized as products. Author’s previous paper presented a method where at each step all the coefficients of the system were transformed. This paper describes a method applicable also to large matrices. Like in revised simplex method, in this method an auxiliary matrix is used for the computations. The algorithm is suitable for unstable and degenerate problems primarily.

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2 Open Mathematics

2 Übi E.

1 2010

1 2007

Wyniki wyszukiwania

Mathematical programming via the least-squares method

On stable least squares solution to the system of linear inequalities