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Instance ex8_1_1

Formatsⓘ ams gms mod nl osil py
Primal Bounds (infeas ≤ 1e-08)ⓘ
-2.02180678 p1 ( gdx sol )
(infeas: 0)
Other points (infeas > 1e-08)ⓘ  
Dual Boundsⓘ
-2.02180678 (COUENNE)
-2.02180678 (LINDO)
-2.0218073 (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.
Adjiman, C S, Dallwig, S, Floudas, C A, and Neumaier, A, A Global Optimization Method, alpha-BB, For General Twice-Differentiable NLPs - I. Theoretical Advances, Computers and Chemical Engineering, 22:9, 1998, 1137-1158.
Sourceⓘ Test Problem ex8.1.1 of Chapter 8 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ⓘ nonlinear
Objective curvatureⓘ indefinite
#Nonzeros in Objectiveⓘ 2
#Nonlinear Nonzeros in Objectiveⓘ 2
#Constraintsⓘ 0
#Linear Constraintsⓘ 0
#Quadratic Constraintsⓘ 0
#Polynomial Constraintsⓘ 0
#Signomial Constraintsⓘ 0
#General Nonlinear Constraintsⓘ 0
Operands in Gen. Nonlin. Functionsⓘ cos div mul sin sqr
Constraints curvatureⓘ linear
#Nonzeros in Jacobianⓘ 0
#Nonlinear Nonzeros in Jacobianⓘ 0
#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+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
*          1        1        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
*          3        1        2        0
*
*  Solve m using NLP minimizing objvar;


Variables  x1,x2,objvar;

Equations  e1;


e1.. -(cos(x1)*sin(x2) - x1/(1 + sqr(x2))) + objvar =E= 0;

* set non-default bounds
x1.lo = -1; x1.up = 2;
x2.lo = -1; x2.up = 1;

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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