MINLPLib

A Library of Mixed-Integer and Continuous Nonlinear Programming Instances

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


Instance ex6_1_2

Formats ams gms mod nl osil py
Primal Bounds (infeas ≤ 1e-08)
-0.03246375 p1 ( gdx sol )
(infeas: 9e-19)
Other points (infeas > 1e-08)  
Dual Bounds
-0.03246663 (ANTIGONE)
-0.03246375 (BARON)
-0.03246753 (COUENNE)
-0.03246375 (LINDO)
-0.03246453 (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.
McDonald, C M and Floudas, C A, Global Optimization for the Phase Stability Problem, AIChE Journal, 41:7, 1995, 1798-1814.
Source Test Problem ex6.1.2 of Chapter 6 of Floudas e.a. handbook
Added to library 31 Jul 2001
Problem type NLP
#Variables 4
#Binary Variables 0
#Integer Variables 0
#Nonlinear Variables 4
#Nonlinear Binary Variables 0
#Nonlinear Integer Variables 0
Objective Sense min
Objective type nonlinear
Objective curvature indefinite
#Nonzeros in Objective 4
#Nonlinear Nonzeros in Objective 4
#Constraints 3
#Linear Constraints 1
#Quadratic Constraints 2
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions log mul
Constraints curvature indefinite
#Nonzeros in Jacobian 8
#Nonlinear Nonzeros in Jacobian 6
#Nonzeros in (Upper-Left) Hessian of Lagrangian 10
#Nonzeros in Diagonal of Hessian of Lagrangian 2
#Blocks in Hessian of Lagrangian 1
Minimal blocksize in Hessian of Lagrangian 4
Maximal blocksize in Hessian of Lagrangian 4
Average blocksize in Hessian of Lagrangian 4.0
#Semicontinuities 0
#Nonlinear Semicontinuities 0
#SOS type 1 0
#SOS type 2 0
Minimal coefficient 2.8750e-02
Maximal coefficient 1.0000e+00
Infeasibility of initial point 1.11e-16
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
*          4        4        0        0        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*          5        5        0        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*         13        3       10        0
*
*  Solve m using NLP minimizing objvar;


Variables  objvar,x2,x3,x4,x5;

Positive Variables  x4,x5;

Equations  e1,e2,e3,e4;


e1.. -((0.06391 + log(x2))*x2 + (-0.02875 + log(x3))*x3 + 0.925356626778358*x2*
     x5 + 0.746014540096753*x3*x4) + objvar =E= 0;

e2.. x4*(x2 + 0.159040857374844*x3) - x2 =E= 0;

e3.. x5*(0.307941026821595*x2 + x3) - x3 =E= 0;

e4..    x2 + x3 =E= 1;

* set non-default bounds
x2.lo = 1E-6; x2.up = 1;
x3.lo = 1E-6; x3.up = 1;

* set non-default levels
x2.l = 0.00421;
x3.l = 0.99579;
x4.l = 0.0258947377097763;
x5.l = 0.998699779997328;

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