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Instance: least

Formats ams gms mod nl osil
Primal Bounds (infeas ≤ 1e-08)
14085.13985000 p1 ( gdx sol )
(infeas: 0)
0.00000000 p2 ( gdx sol )
(infeas: 0)
Other points (infeas > 1e-08)  
Dual Bounds
0.00000000 (ANTIGONE)
0.00000000 (BARON)
0.00000000 (COUENNE)
0.00000000 (SCIP)
References Bracken, Jerome and McCormick, Garth P, Chapter 8.4. In Bracken, Jerome and McCormick, Garth P, Selected Applications of Nonlinear Programming, John Wiley and Sons, New York, 1968, 89-90.
Source GAMS Model Library model least
Application Statistics
Added to library 31 Jul 2001
Problem type NLP
#Variables 3
#Binary Variables 0
#Integer Variables 0
#Nonlinear Variables 3
#Nonlinear Binary Variables 0
#Nonlinear Integer Variables 0
Objective Sense min
Objective type nonlinear
Objective curvature indefinite
#Nonzeros in Objective 3
#Nonlinear Nonzeros in Objective 3
#Constraints 0
#Linear Constraints 0
#Quadratic Constraints 0
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions mul exp sqr
Constraints curvature linear
#Nonzeros in Jacobian 0
#Nonlinear Nonzeros in Jacobian 0
#Nonzeros in (Upper-Left) Hessian of Lagrangian 9
#Nonzeros in Diagonal of Hessian of Lagrangian 3
#Blocks in Hessian of Lagrangian 1
Minimal blocksize in Hessian of Lagrangian 3
Maximal blocksize in Hessian of Lagrangian 3
Average blocksize in Hessian of Lagrangian 3.0
#Semicontinuities 0
#Nonlinear Semicontinuities 0
#SOS type 1 0
#SOS type 2 0
Infeasibility of initial point 0
Sparsity Jacobian Sparsity of Objective Gradient and Jacobian
Sparsity Hessian of Lagrangian Sparsity of Hessian of Lagrangian

$offlisting
*  
*  Equation counts
*      Total        E        G        L        N        X        C        B
*          1        1        0        0        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*          4        4        0        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*          4        1        3        0
*
*  Solve m using NLP minimizing objvar;


Variables  objvar,x2,x3,x4;

Equations  e1;


e1.. -(sqr(127 - exp(-5*x4)*x3 - x2) + sqr(151 - exp(-3*x4)*x3 - x2) + sqr(379
      - exp(-x4)*x3 - x2) + sqr(421 - exp(5*x4)*x3 - x2) + sqr(460 - exp(3*x4)*
     x3 - x2) + sqr(426 - exp(x4)*x3 - x2)) + objvar =E= 0;

* set non-default bounds
x4.lo = -5; x4.up = 5;

* set non-default levels
x2.l = 500;
x3.l = -150;
x4.l = -0.2;

Model m / all /;

m.limrow=0; m.limcol=0;
m.tolproj=0.0;

$if NOT '%gams.u1%' == '' $include '%gams.u1%'

$if not set NLP $set NLP NLP
Solve m using %NLP% minimizing objvar;


Last updated: 2019-09-10 Git hash: 87a8f78d
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