By perturbing properly a linear program to a separable quadratic program, it is possible to solve the latter in its dual variable space by iterative techniques such as sparsity-preserving SOR (successive overrelaxation) algorithms. The main result of this paper gives an effective computational criterion to check whether the solutions of the perturbed quadratic programs provide the least-norm solution of the original linear program.
A New Result in the Theory and Computation of the Least Norm Solution of a Linear Programm / Lucidi, Stefano. - In: JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS. - ISSN 0022-3239. - STAMPA. - 55:(1987), pp. 103-117. [10.1007/BF00939047]
A New Result in the Theory and Computation of the Least Norm Solution of a Linear Programm
LUCIDI, Stefano
1987
Abstract
By perturbing properly a linear program to a separable quadratic program, it is possible to solve the latter in its dual variable space by iterative techniques such as sparsity-preserving SOR (successive overrelaxation) algorithms. The main result of this paper gives an effective computational criterion to check whether the solutions of the perturbed quadratic programs provide the least-norm solution of the original linear program.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
