Showing papers by "Leon S. Lasdon published in 1992"
TL;DR: In this paper, a nonlinear dynamic data reconciliation (NDDR) algorithm using nonlinear programming is proposed to reduce the level of process variable corruption due to measurement noise and improve both process knowledge and control system performance.
259 citations
TL;DR: A feasibility-retaining GRG algorithm for large sparse nonlinear programs of general form, enhanced by heuristics which aid in basis selection, combatting degeneracy, dynamic tolerance adjustment, and predicting Newton failures is described.
Abstract: We describe a feasibility-retaining GRG algorithm for large sparse nonlinear programs of general form. Its FORTRAN implementation, LSGRG, is enhanced by heuristics which aid in basis selection, combatting degeneracy, dynamic tolerance adjustment, and predicting Newton failures. Key roles are also played by efficient procedures for basis inversion and by both pure and limited memory BFGS methods for computing the search direction. The design goal for LSGRG is maximum reliability with at least acceptable speed. Extensive computational tests on both FORTRAN and GAMS models indicate that LSGRG is promising in this regard. Comparisons are presented with GRG2, a sparsity oriented SQP code, and MINOS, indicating that LSGRG is a useful complement to MINOS in a multi-solver NLP environment. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
179 citations
TL;DR: A procedure is described which determines Jacobian incidence structure and the constant/nonconstant nature of each Jacobian element via examination of the text of function expression strings via examination for algebraic modelling systems and other systems with interpreted functions which require evaluation of first derivatives.
Abstract: A procedure is described which determines Jacobian incidence structure and the constant/nonconstant nature of each Jacobian element via examination of the text of function expression strings. This procedure may be used to minimize the effort required to evaluate by finite differences the Jacobian of a set of functions. Target applications involve algebraic modelling systems and other systems with interpreted functions which require evaluation of first derivatives. Computational experience is presented and discussed.