An extension of the generalized reduced gradient (GRG) method to large scale nonlinear programs with nonlinear constraints is discussed. The approach presented here represents the adoption of efficient methods for sparse matrices within the framework of the GRG algorithm. The resulting code, LGOPT, is described, and experience with a class of minimum weight structural problems is given.
Large Scale Nonlinear Programming Using The Generalized Reduced Gradient Method
G. A. Gabriele,
G. A. Gabriele
U. S. Army Computer Systems Command, Georgia Institute of Technology, Atlanta, Ga.
K. M. Ragsdell
School of Mechanical Engineering, Purdue University, West Lafayette, Ind.
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Gabriele, G. A., and Ragsdell, K. M. (July 1, 1980). "Large Scale Nonlinear Programming Using The Generalized Reduced Gradient Method." ASME. J. Mech. Des. July 1980; 102(3): 566–573. https://doi.org/10.1115/1.3254786
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