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.

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