Reverse communication version of PORT's MNG. Finds a local minimum of a continuously differentiable function. User supplies gradient of objective function. Secant Hessian approximations are used. Uses a variant of Newton's method with a quasi-Newton (BFGS) Hessian updating method, and a model/trust-region technique to aid convergence from poor starting values. Classes : G1b1b . Unconstrained optimization of a smooth multivariate function, user provides first derivatives Type : Fortran subroutine in PORT library (NL3OPT sublibrary). Access : Proprietary. Many implementations available. Precision: Double. Usage : CALL DRMNG (D, FX, G, IV, LIV, LV, N, V, X) Details : Fullsource Source Sites : (1) NETLIB
NETLIB: Public access repository, The University of Tennessee at Knoxville and Bell Laboratories Precision: Double. (Single: RMNG) You may access components from NETLIB outside GAMS as follows. Source : Available by anonymous ftp from netlib in the port subdirectory Fullsource : Available by http from netlib in the port subdirectory
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