MINLPLib

A Library of Mixed-Integer and Continuous Nonlinear Programming Instances

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Instance: st_e22

Formats ams gms lp mod nl osil pip
Primal Bounds (infeas ≤ 1e-08)
-68.00000000 p1 ( gdx sol )
(infeas: 9e-16)
-85.00000000 p2 ( gdx sol )
(infeas: 0)
Other points (infeas > 1e-08)  
Dual Bounds
-85.00000008 (ANTIGONE)
-85.00000008 (BARON)
-85.00000002 (COUENNE)
-85.00000000 (LINDO)
-85.00000853 (SCIP)
References Tawarmalani, M and Sahinidis, N V, Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming: Theory, Algorithms, Software, and Applications, Kluwer, 2002.
Kalantari, B and Rosen, J B, An Algorithm for Global Minimization of Linearly Constrained Concave Quadratic Functions, Mathematics of Operations Research, 12:3, 1987, 544-561.
Source BARON book instance misc/e22
Added to library 03 Sep 2002
Problem type QP
#Variables 2
#Binary Variables 0
#Integer Variables 0
#Nonlinear Variables 2
#Nonlinear Binary Variables 0
#Nonlinear Integer Variables 0
Objective Sense min
Objective type quadratic
Objective curvature concave
#Nonzeros in Objective 2
#Nonlinear Nonzeros in Objective 2
#Constraints 5
#Linear Constraints 5
#Quadratic Constraints 0
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions  
Constraints curvature linear
#Nonzeros in Jacobian 10
#Nonlinear Nonzeros in Jacobian 0
#Nonzeros in (Upper-Left) Hessian of Lagrangian 2
#Nonzeros in Diagonal of Hessian of Lagrangian 2
#Blocks in Hessian of Lagrangian 2
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
Infeasibility of initial point 4
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
*          6        1        0        5        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*          3        3        0        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*         13       11        2        0
*
*  Solve m using NLP minimizing objvar;


Variables  x1,x2,objvar;

Positive Variables  x1,x2;

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


e1..    x1 + x2 =L= 10;

e2..    x1 + 5*x2 =L= 22;

e3..  - 3*x1 + 2*x2 =L= 2;

e4..  - x1 - 4*x2 =L= -4;

e5..    x1 - 2*x2 =L= 4;

e6.. -(-sqr(x1) - 4*sqr(x2)) + objvar =E= 0;

* set non-default bounds
x1.up = 8;
x2.up = 4;

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: 2019-07-12 Git hash: 46a7b4f1
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