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Instance: ex5_2_2_case2

Formats ams gms lp mod nl osil pip
Primal Bounds
-0.00000000 p1 ( gdx sol )
(infeas: 0)
-400.00000000 p2 ( gdx sol )
(infeas: 1e-14)
-600.00000000 p3 ( gdx sol )
(infeas: 0)
Dual Bounds
-600.00000060 (ANTIGONE)
-600.00000060 (BARON)
-600.00000060 (COUENNE)
-600.00000000 (LINDO)
-600.00000020 (SCIP)
References Floudas, C A, Pardalos, Panos M, Adjiman, C S, Esposito, W R, Gumus, Zeynep H, Harding, S T, Klepeis, John L, Meyer, Clifford A, and Schweiger, C A, Handbook of Test Problems in Local and Global Optimization, Kluwer Academic Publishers, 1999.
Haverly, C A, Studies of the Behavior of Recursion for the Pooling Problem, ACM SIGMAP Bull, 25, 1978, 19-28.
Source Test Problem ex5.2.2_case2 of Chapter 5 of Floudas e.a. handbook
Added to library 31 Jul 2001
Problem type QCP
#Variables 9
#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 6
#Nonlinear Nonzeros in Objective 0
#Constraints 6
#Linear Constraints 3
#Quadratic Constraints 3
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions  
Constraints curvature indefinite
#Nonzeros in Jacobian 23
#Nonlinear Nonzeros in Jacobian 7
#Nonzeros in (Upper-Left) Hessian of Lagrangian 4
#Nonzeros in Diagonal of Hessian of Lagrangian 0
#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
*          7        5        0        2        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*         10       10        0        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*         30       23        7        0
*
*  Solve m using NLP minimizing objvar;


Variables  x1,x2,x3,x4,x5,x6,x7,x8,x9,objvar;

Positive Variables  x1,x2,x3,x4,x5,x6,x7,x8,x9;

Equations  e1,e2,e3,e4,e5,e6,e7;


e1..  - 9*x1 - 15*x2 + 6*x3 + 16*x4 + 10*x5 + 10*x6 - objvar =E= 0;

e2..  - x3 - x4 + x8 + x9 =E= 0;

e3..    x1 - x5 - x8 =E= 0;

e4..    x2 - x6 - x9 =E= 0;

e5.. x7*x8 - 2.5*x1 + 2*x5 =L= 0;

e6.. x7*x9 - 1.5*x2 + 2*x6 =L= 0;

e7.. x7*x8 + x7*x9 - 3*x3 - x4 =E= 0;

* set non-default bounds
x1.up = 600;
x2.up = 200;
x3.up = 500;
x4.up = 500;
x5.up = 500;
x6.up = 500;
x7.up = 500;
x8.up = 500;
x9.up = 500;

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: 2018-09-14 Git hash: ac5a5314
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