Module MNGB in PORT

• PORT Information

• Components
  • Fullsource from NETLIB
  • Source from NETLIB

MNGB

 
Finds a local minimum of a continuously differentiable function subject to
simple upper and lower bound constraints. 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  :  G2h1a2 . General nonlinear optimization with simple bounds of a
                   smooth function, user provides first derivatives
 
Type     : Fortran subroutine in PORT library (NL2OPT sublibrary).
Access   : Proprietary. Many implementations available.
Precision: Single.
 
Usage    : CALL MNGB (N, D, X, B, CALCF, CALCG, IV, LIV, LV, V, UIPARM, URPARM,
           UFPARM)
 
Details  : Fullsource Source
Sites    : (1) NETLIB
 

Implementation of MNGB from PORT on NETLIB

 
NETLIB:    Public access repository, The University of Tennessee at
           Knoxville and Bell Laboratories
 
Precision: Single. (Double: DMNGB)
 
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