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Instance: circle

Formats ams gms lp mod nl osil pip
Primal Bounds
4.57424778 p1 ( gdx sol )
(infeas: 0)
Dual Bounds
4.57424778 (ANTIGONE)
4.57424777 (BARON)
4.57424778 (COUENNE)
4.57424778 (LINDO)
4.57424774 (SCIP)
References Gill, Philip E, Murray, Walter, Saunders, M A, Drud, Arne S, and Kalvelagen, Erwin, GAMS/SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization, 2002.
Source GAMS Model Library model circle
Application Geometry
Added to library 31 Jul 2001
Problem type QCP
#Variables 3
#Binary Variables 0
#Integer Variables 0
#Nonlinear Variables 3
#Nonlinear Binary Variables 0
#Nonlinear Integer Variables 0
Objective Sense min
Objective type linear
Objective curvature linear
#Nonzeros in Objective 1
#Nonlinear Nonzeros in Objective 0
#Constraints 10
#Linear Constraints 0
#Quadratic Constraints 10
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions  
Constraints curvature indefinite
#Nonzeros in Jacobian 30
#Nonlinear Nonzeros in Jacobian 30
#Nonzeros in (Upper-Left) Hessian of Lagrangian 3
#Nonzeros in Diagonal of Hessian of Lagrangian 3
#Blocks in Hessian of Lagrangian 3
Minimal blocksize in Hessian of Lagrangian 1
Maximal blocksize in Hessian of Lagrangian 1
Average blocksize in Hessian of Lagrangian 1.0
#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
*         10        0        0       10        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*          3        3        0        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*         30        0       30        0
*
*  Solve m using NLP minimizing objvar;


Variables  x1,x2,objvar;

Equations  e1,e2,e3,e4,e5,e6,e7,e8,e9,e10;


e1.. sqr(2.545724188 - x1) + sqr(9.983058643 - x2) - sqr(objvar) =L= 0;

e2.. sqr(8.589400372 - x1) + sqr(6.208600402 - x2) - sqr(objvar) =L= 0;

e3.. sqr(5.953378204 - x1) + sqr(9.920197351 - x2) - sqr(objvar) =L= 0;

e4.. sqr(3.710241136 - x1) + sqr(7.860254203 - x2) - sqr(objvar) =L= 0;

e5.. sqr(3.629909053 - x1) + sqr(2.176232347 - x2) - sqr(objvar) =L= 0;

e6.. sqr(3.016475803 - x1) + sqr(6.757468831 - x2) - sqr(objvar) =L= 0;

e7.. sqr(4.148474536 - x1) + sqr(2.435660776 - x2) - sqr(objvar) =L= 0;

e8.. sqr(8.706433123 - x1) + sqr(3.250724797 - x2) - sqr(objvar) =L= 0;

e9.. sqr(1.604023507 - x1) + sqr(7.020357481 - x2) - sqr(objvar) =L= 0;

e10.. sqr(5.501896021 - x1) + sqr(4.918207429 - x2) - sqr(objvar) =L= 0;

* set non-default bounds
objvar.lo = 0;

* set non-default levels
x1.l = 5.155228315;
x2.l = 5.793541075;
objvar.l = 5.49209550544626;

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: 2018-08-07 Git hash: fccdb193
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