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A Library of Mixed-Integer and Continuous Nonlinear Programming Instances

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Instance st_e07

Formats ams gms lp mod nl osil pip py
Primal Bounds (infeas ≤ 1e-08)
-400.00000000 p1 ( gdx sol )
(infeas: 0)
Other points (infeas > 1e-08)  
Dual Bounds
-400.00000040 (ANTIGONE)
-400.00000040 (BARON)
-400.00000000 (COUENNE)
-400.00000000 (GUROBI)
-400.00000000 (LINDO)
-400.00000000 (SCIP)
References Haverly, C A, Studies of the Behavior of Recursion for the Pooling Problem, ACM SIGMAP Bull, 25, 1978, 19-28.
Tawarmalani, M and Sahinidis, N V, Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming: Theory, Algorithms, Software, and Applications, Kluwer, 2002.
Source BARON book instance misc/e07
Added to library 03 Sep 2002
Problem type QCP
#Variables 10
#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 5
#Nonlinear Nonzeros in Objective 0
#Constraints 7
#Linear Constraints 4
#Quadratic Constraints 3
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions  
Constraints curvature indefinite
#Nonzeros in Jacobian 26
#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
Minimal coefficient 1.0000e+00
Maximal coefficient 1.6000e+01
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
*          8        6        0        2        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*         11       11        0        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*         32       25        7        0
*
*  Solve m using NLP minimizing objvar;


Variables  x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,objvar;

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

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


e1..    x1 + x2 - x3 - x4 =E= 0;

e2..    x3 - x5 + x7 =E= 0;

e3..    x4 + x8 - x9 =E= 0;

e4..  - x6 + x7 + x8 =E= 0;

e5.. x10*x3 - 2.5*x5 + 2*x7 =L= 0;

e6.. x10*x4 + 2*x8 - 1.5*x9 =L= 0;

e7.. -x10*(x3 + x4) + 3*x1 + x2 =E= 0;

e8..  - 6*x1 - 16*x2 + 9*x5 - 10*x6 + 15*x9 + objvar =E= 0;

* set non-default bounds
x1.up = 300;
x2.up = 300;
x3.up = 100;
x4.up = 200;
x5.up = 100;
x6.up = 300;
x7.up = 100;
x8.up = 200;
x9.up = 200;
x10.lo = 1; x10.up = 3;

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;


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