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A Library of Mixed-Integer and Continuous Nonlinear Programming Instances

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Instance ex3_1_3

Formats ams gms lp mod nl osil pip py
Primal Bounds (infeas ≤ 1e-08)
-310.00000000 p1 ( gdx sol )
(infeas: 0)
Other points (infeas > 1e-08)  
Dual Bounds
-310.00000030 (ANTIGONE)
-310.00010110 (BARON)
-310.00000010 (COUENNE)
-310.00000000 (GUROBI)
-310.00000000 (LINDO)
-310.00003740 (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.
Hesse, R, A Heuristic Search Procedure for Estimating a Global Solution of Nonconvex Programming Problems, Operations Research, 21:6, 1973, 1267--1280.
Source Test Problem ex3.1.3 of Chapter 3 of Floudas e.a. handbook
Added to library 31 Jul 2001
Problem type QCQP
#Variables 6
#Binary Variables 0
#Integer Variables 0
#Nonlinear Variables 6
#Nonlinear Binary Variables 0
#Nonlinear Integer Variables 0
Objective Sense min
Objective type quadratic
Objective curvature concave
#Nonzeros in Objective 6
#Nonlinear Nonzeros in Objective 6
#Constraints 6
#Linear Constraints 4
#Quadratic Constraints 2
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions  
Constraints curvature concave
#Nonzeros in Jacobian 12
#Nonlinear Nonzeros in Jacobian 2
#Nonzeros in (Upper-Left) Hessian of Lagrangian 6
#Nonzeros in Diagonal of Hessian of Lagrangian 6
#Blocks in Hessian of Lagrangian 6
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
Minimal coefficient 1.0000e+00
Maximal coefficient 2.5000e+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
*          7        1        3        3        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*          7        7        0        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*         19       11        8        0
*
*  Solve m using NLP minimizing objvar;


Variables  x1,x2,x3,x4,x5,x6,objvar;

Positive Variables  x1,x2,x4,x6;

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


e1.. -(-25*sqr((-2) + x1) - sqr((-2) + x2) - sqr((-1) + x3) - sqr((-4) + x4) - 
     sqr((-1) + x5) - sqr((-4) + x6)) + objvar =E= 0;

e2.. sqr((-3) + x3) + x4 =G= 4;

e3.. sqr((-3) + x5) + x6 =G= 4;

e4..    x1 - 3*x2 =L= 2;

e5..  - x1 + x2 =L= 2;

e6..    x1 + x2 =L= 6;

e7..    x1 + x2 =G= 2;

* set non-default bounds
x3.lo = 1; x3.up = 5;
x4.up = 6;
x5.lo = 1; x5.up = 5;
x6.up = 10;

* set non-default levels
x1.l = 5;
x2.l = 1;
x3.l = 5;
x5.l = 5;
x6.l = 10;

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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