MINLPLib

A Library of Mixed-Integer and Continuous Nonlinear Programming Instances

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


Removed Instance sample

Formats ams gms mod nl osil py
Primal Bounds (infeas ≤ 1e-08)
726.67935690 p1 ( gdx sol )
(infeas: 2e-11)
Other points (infeas > 1e-08)
726.67041020 p2 ( gdx sol )
(infeas: 4e-07)
Dual Bounds
726.67935690 (ANTIGONE)
726.67935620 (BARON)
726.67437440 (COUENNE)
726.67935690 (LINDO)
726.67689980 (SCIP)
References Bracken, Jerome and McCormick, Garth P, Chapter 10.2. In Bracken, Jerome and McCormick, Garth P, Selected Applications of Nonlinear Programming, John Wiley and Sons, New York, 1968.
Source GAMS Model Library model sample
Application Stratified Sample Design
Added to library 31 Jul 2001
Removed from library 16 Feb 2022
Removed because Instance is continuous and convex.
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 linear
Objective curvature linear
#Nonzeros in Objective 4
#Nonlinear Nonzeros in Objective 0
#Constraints 2
#Linear Constraints 0
#Quadratic Constraints 0
#Polynomial Constraints 0
#Signomial Constraints 2
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions  
Constraints curvature convex
#Nonzeros in Jacobian 8
#Nonlinear Nonzeros in Jacobian 8
#Nonzeros in (Upper-Left) Hessian of Lagrangian 4
#Nonzeros in Diagonal of Hessian of Lagrangian 4
#Blocks in Hessian of Lagrangian 4
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 1.6000e-01
Maximal coefficient 4.0000e+00
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
*          3        1        0        2        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        5        8        0
*
*  Solve m using NLP minimizing objvar;


Variables  x1,x2,x3,x4,objvar;

Equations  e1,e2,e3;


e1.. 4/x1 + 2.25/x2 + 1/x3 + 0.25/x4 =L= 0.0401;

e2.. 0.16/x1 + 0.36/x2 + 0.64/x3 + 0.64/x4 =L= 0.010085;

e3..  - x1 - x2 - x3 - x4 + objvar =E= 0;

* set non-default bounds
x1.lo = 100; x1.up = 400000;
x2.lo = 100; x2.up = 300000;
x3.lo = 100; x3.up = 200000;
x4.lo = 100; x4.up = 100000;

* set non-default levels
x1.l = 200;
x2.l = 200;
x3.l = 200;
x4.l = 200;
objvar.l = 800;

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: 2024-12-17 Git hash: 8eaceb91
Imprint / Privacy Policy / License: CC-BY 4.0