MINLPLib

A Library of Mixed-Integer and Continuous Nonlinear Programming Instances

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Instance ex8_5_4

Formatsⓘ	ams gms mod nl osil py
Primal Bounds (infeas ≤ 1e-08)ⓘ	0.00000101 p1 ( gdx sol ) (infeas: 3e-14) -0.00042515 p2 ( gdx sol ) (infeas: 1e-16)
Other points (infeas > 1e-08)ⓘ
Dual Boundsⓘ	-0.00042603 (BARON) -0.00042515 (COUENNE) -0.00042515 (LINDO) -0.00042667 (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. Hua, J, Brennecke, J, and Stadtherr, M, Enhanced Interval Analysis for Phase Stability: Cubic Equation of State Models, Industrial and Engineering Chemistry Research, 37:4, 1998, 1519-1527.
Sourceⓘ	Test Problem ex8.5.4 of Chapter 8 of Floudas e.a. handbook
Added to libraryⓘ	31 Jul 2001
Problem typeⓘ	NLP
#Variablesⓘ	5
#Binary Variablesⓘ	0
#Integer Variablesⓘ	0
#Nonlinear Variablesⓘ	5
#Nonlinear Binary Variablesⓘ	0
#Nonlinear Integer Variablesⓘ	0
Objective Senseⓘ	min
Objective typeⓘ	nonlinear
Objective curvatureⓘ	unknown
#Nonzeros in Objectiveⓘ	5
#Nonlinear Nonzeros in Objectiveⓘ	5
#Constraintsⓘ	4
#Linear Constraintsⓘ	2
#Quadratic Constraintsⓘ	1
#Polynomial Constraintsⓘ	1
#Signomial Constraintsⓘ	0
#General Nonlinear Constraintsⓘ	0
Operands in Gen. Nonlin. Functionsⓘ	div log mul
Constraints curvatureⓘ	indefinite
#Nonzeros in Jacobianⓘ	11
#Nonlinear Nonzeros in Jacobianⓘ	5
#Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ	12
#Nonzeros in Diagonal of Hessian of Lagrangianⓘ	4
#Blocks in Hessian of Lagrangianⓘ	2
Minimal blocksize in Hessian of Lagrangianⓘ	2
Maximal blocksize in Hessian of Lagrangianⓘ	3
Average blocksize in Hessian of Lagrangianⓘ	2.5
#Semicontinuitiesⓘ	0
#Nonlinear Semicontinuitiesⓘ	0
#SOS type 1ⓘ	0
#SOS type 2ⓘ	0
Minimal coefficientⓘ	1.2932e-01
Maximal coefficientⓘ	3.2753e+00
Infeasibility of initial pointⓘ	1
Sparsity Jacobianⓘ
Sparsity Hessian of Lagrangianⓘ

$offlisting
*  
*  Equation counts
*      Total        E        G        L        N        X        C        B
*          5        5        0        0        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*          6        6        0        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*         17        7       10        0
*
*  Solve m using NLP minimizing objvar;


Variables  objvar,x2,x3,x4,x5,x6;

Equations  e1,e2,e3,e4,e5;


e1.. -(log(x2)*x2 + log(x3)*x3 - log(x4 - x6) + x4 - log(1 + x6/x4)*x5/x6 + 
     0.362259780811985*x2 + 3.27527428318836*x3) + objvar =E= -1;

e2.. POWER(x4,3) - sqr(x4) + (-sqr(x6) - x6 + x5)*x4 - x5*x6 =E= 0;

e3.. -(0.352565*x2*x2 + 0.844083*x2*x3 + 0.844083*x3*x2 + 2.14335*x3*x3) + x5
      =E= 0;

e4..  - 0.12932*x2 - 0.271567*x3 + x6 =E= 0;

e5..    x2 + x3 =E= 1;

* set non-default levels
x2.l = 0.5;
x3.l = 0.5;
x4.l = 2;
x5.l = 1;
x6.l = 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;