MINLPLib

A Library of Mixed-Integer and Continuous Nonlinear Programming Instances

Home // Instances // Documentation // Download // Statistics


Instance ex1225

Formats ams gms mod nl osil py
Primal Bounds (infeas ≤ 1e-08)
31.00000000 p1 ( gdx sol )
(infeas: 0)
Other points (infeas > 1e-08)  
Dual Bounds
31.00000000 (ANTIGONE)
31.00000000 (BARON)
31.00000000 (COUENNE)
31.00000000 (LINDO)
31.00000000 (SCIP)
27.00000000 (SHOT)
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.
Pörn, Ray, Harjunkoski, Iiro, and Westerlund, Tapio, Convexification of Different Classes of Non-Convex MINLP Problems, Computers and Chemical Engineering, 23:3, 1999, 439-448.
Source Test Problem ex12.2.5 of Chapter 12 of Floudas e.a. handbook
Added to library 01 May 2001
Problem type MBNLP
#Variables 8
#Binary Variables 6
#Integer Variables 0
#Nonlinear Variables 2
#Nonlinear Binary Variables 0
#Nonlinear Integer Variables 0
Objective Sense min
Objective type linear
Objective curvature linear
#Nonzeros in Objective 2
#Nonlinear Nonzeros in Objective 0
#Constraints 10
#Linear Constraints 9
#Quadratic Constraints 0
#Polynomial Constraints 0
#Signomial Constraints 1
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions  
Constraints curvature indefinite
#Nonzeros in Jacobian 24
#Nonlinear Nonzeros in Jacobian 2
#Nonzeros in (Upper-Left) Hessian of Lagrangian 4
#Nonzeros in Diagonal of Hessian of Lagrangian 2
#Blocks in Hessian of Lagrangian 1
Minimal blocksize in Hessian of Lagrangian 2
Maximal blocksize in Hessian of Lagrangian 2
Average blocksize in Hessian of Lagrangian 2.0
#Semicontinuities 0
#Nonlinear Semicontinuities 0
#SOS type 1 0
#SOS type 2 0
Minimal coefficient 1.0000e+00
Maximal coefficient 1.0000e+01
Infeasibility of initial point 9
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
*         11        3        0        8        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*          9        3        6        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*         27       25        2        0
*
*  Solve m using MINLP minimizing objvar;


Variables  x1,x2,b3,b4,b5,b6,b7,b8,objvar;

Binary Variables  b3,b4,b5,b6,b7,b8;

Equations  e1,e2,e3,e4,e5,e6,e7,e8,e9,e10,e11;


e1..  - 7*x1 - 10*x2 + objvar =E= 0;

e2.. x1**1.2*x2**1.7 - 7*x1 - 9*x2 =L= -24;

e3..  - x1 - 2*x2 =L= -5;

e4..  - 3*x1 + x2 =L= 1;

e5..    4*x1 - 3*x2 =L= 11;

e6..    x1 - b3 - 2*b4 - 4*b5 =E= 1;

e7..    x2 - b6 - 2*b7 - 4*b8 =E= 1;

e8..    b3 + b5 =L= 1;

e9..    b6 + b8 =L= 1;

e10..    b4 + b5 =L= 1;

e11..    b7 + b8 =L= 1;

* set non-default bounds
x1.lo = 1; x1.up = 5;
x2.lo = 1; x2.up = 5;

Model m / all /;

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

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

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


Last updated: 2024-03-25 Git hash: 1dae024f
Imprint / Privacy Policy / License: CC-BY 4.0