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A Library of Mixed-Integer and Continuous Nonlinear Programming Instances

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Instance ex4_1_8

Formatsⓘ ams gms mod nl osil pip py
Primal Bounds (infeas ≤ 1e-08)ⓘ
-16.73889318 p1 ( gdx sol )
(infeas: 0)
Other points (infeas > 1e-08)ⓘ  
Dual Boundsⓘ
-16.73889366 (ANTIGONE)
-16.7388932 (BARON)
-16.73889318 (COUENNE)
-16.73889318 (LINDO)
-16.73889328 (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.
Soland, R M, An Algorithm for Separable Nonconvex Programming Problems II: Nonconvex Constraints, Management Science, 17:11, 1971, 759-773.
Sourceⓘ Test Problem ex4.1.8 of Chapter 4 of Floudas e.a. handbook
Added to libraryⓘ 31 Jul 2001
Problem typeⓘ NLP
#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ⓘ convex
#Nonzeros in Objectiveⓘ 2
#Nonlinear Nonzeros in Objectiveⓘ 1
#Constraintsⓘ 1
#Linear Constraintsⓘ 0
#Quadratic Constraintsⓘ 0
#Polynomial Constraintsⓘ 1
#Signomial Constraintsⓘ 0
#General Nonlinear Constraintsⓘ 0
Operands in Gen. Nonlin. Functionsⓘ  
Constraints curvatureⓘ indefinite
#Nonzeros in Jacobianⓘ 2
#Nonlinear Nonzeros in Jacobianⓘ 1
#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
Minimal coefficientⓘ 1.0000e+00
Maximal coefficientⓘ 1.2000e+01
Infeasibility of initial pointⓘ 5.095e-05
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
*          2        2        0        0        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
*          5        3        2        0
*
*  Solve m using NLP minimizing objvar;


Variables  x1,x2,objvar;

Positive Variables  x1,x2;

Equations  e1,e2;


e1.. -(sqr(x2) - 7*x2) + 12*x1 + objvar =E= 0;

e2.. -2*POWER(x1,4) - x2 =E= -2;

* set non-default bounds
x1.up = 2;
x2.up = 3;

* set non-default levels
x1.l = 0.7175;
x2.l = 1.47;

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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