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Instance ex14_2_8
Formatsⓘ | ams gms mod nl osil py |
Primal Bounds (infeas ≤ 1e-08)ⓘ | |
Other points (infeas > 1e-08)ⓘ | |
Dual Boundsⓘ | -0.00000000 (ANTIGONE) -0.00000000 (BARON) 0.00000000 (COUENNE) 0.00000000 (LINDO) 0.00000000 (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. |
Sourceⓘ | Test Problem ex14.2.8 of Chapter 14 of Floudas e.a. handbook |
Added to libraryⓘ | 31 Jul 2001 |
Problem typeⓘ | NLP |
#Variablesⓘ | 4 |
#Binary Variablesⓘ | 0 |
#Integer Variablesⓘ | 0 |
#Nonlinear Variablesⓘ | 3 |
#Nonlinear Binary Variablesⓘ | 0 |
#Nonlinear Integer Variablesⓘ | 0 |
Objective Senseⓘ | min |
Objective typeⓘ | linear |
Objective curvatureⓘ | linear |
#Nonzeros in Objectiveⓘ | 1 |
#Nonlinear Nonzeros in Objectiveⓘ | 0 |
#Constraintsⓘ | 5 |
#Linear Constraintsⓘ | 1 |
#Quadratic Constraintsⓘ | 0 |
#Polynomial Constraintsⓘ | 0 |
#Signomial Constraintsⓘ | 0 |
#General Nonlinear Constraintsⓘ | 4 |
Operands in Gen. Nonlin. Functionsⓘ | div log |
Constraints curvatureⓘ | indefinite |
#Nonzeros in Jacobianⓘ | 18 |
#Nonlinear Nonzeros in Jacobianⓘ | 12 |
#Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 5 |
#Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 3 |
#Blocks in Hessian of Lagrangianⓘ | 2 |
Minimal blocksize in Hessian of Lagrangianⓘ | 1 |
Maximal blocksize in Hessian of Lagrangianⓘ | 2 |
Average blocksize in Hessian of Lagrangianⓘ | 1.5 |
#Semicontinuitiesⓘ | 0 |
#Nonlinear Semicontinuitiesⓘ | 0 |
#SOS type 1ⓘ | 0 |
#SOS type 2ⓘ | 0 |
Minimal coefficientⓘ | 2.1679e-02 |
Maximal coefficientⓘ | 2.7875e+03 |
Infeasibility of initial pointⓘ | 3.997e-05 |
Sparsity Jacobianⓘ | |
Sparsity Hessian of Lagrangianⓘ |
$offlisting * * Equation counts * Total E G L N X C B * 6 2 0 4 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 * 20 8 12 0 * * Solve m using NLP minimizing objvar; Variables x1,x2,x3,objvar,x5; Positive Variables x5; Equations e1,e2,e3,e4,e5,e6; e1.. objvar - x5 =E= 0; e2.. 10.68*log(2.5735*x1 + 4.0464*x2) - 9.344*log(2.336*x1 + 3.24*x2) - ( 2.5364416*x2 - 0.993370999999997*x1)/(2.5735*x1 + 4.0464*x2) - (1.696*log( 1.69610217540928*x1 + 3.24*x2) + 0.64*log(0.657731453039811*x1 + 0.0338737664203932*x2)) - (2.87658928949414*x1/(1.69610217540928*x1 + 3.24 *x2) + 5.49537104832607*x2/(1.69610217540928*x1 + 3.24*x2) + 0.420948129945479*x1/(0.657731453039811*x1 + 0.0338737664203932*x2)) - 2787.49800065313/(229.664 + x3) - x5 =L= -10.164795069335; e3.. 15.2*log(2.5735*x1 + 4.0464*x2) - 12.96*log(2.336*x1 + 3.24*x2) - ( 3.98813184*x2 - 1.5619104*x1)/(2.5735*x1 + 4.0464*x2) - 3.24*log( 1.69610217540928*x1 + 3.24*x2) - (5.49504*x1/(1.69610217540928*x1 + 3.24* x2) + 10.4976*x2/(1.69610217540928*x1 + 3.24*x2) + 0.0216792105090516*x1/( 0.657731453039811*x1 + 0.0338737664203932*x2)) - 2766.63/(222.65 + x3) - x5 =L= -11.1422900361581; e4.. 9.344*log(2.336*x1 + 3.24*x2) - 10.68*log(2.5735*x1 + 4.0464*x2) + ( 2.5364416*x2 - 0.993370999999997*x1)/(2.5735*x1 + 4.0464*x2) + 1.696*log( 1.69610217540928*x1 + 3.24*x2) + 0.64*log(0.657731453039811*x1 + 0.0338737664203932*x2) + 2.87658928949414*x1/(1.69610217540928*x1 + 3.24* x2) + 5.49537104832607*x2/(1.69610217540928*x1 + 3.24*x2) + 0.420948129945479*x1/(0.657731453039811*x1 + 0.0338737664203932*x2) + 2787.49800065313/(229.664 + x3) - x5 =L= 10.164795069335; e5.. 12.96*log(2.336*x1 + 3.24*x2) - 15.2*log(2.5735*x1 + 4.0464*x2) + ( 3.98813184*x2 - 1.5619104*x1)/(2.5735*x1 + 4.0464*x2) + 3.24*log( 1.69610217540928*x1 + 3.24*x2) + 5.49504*x1/(1.69610217540928*x1 + 3.24*x2 ) + 10.4976*x2/(1.69610217540928*x1 + 3.24*x2) + 0.0216792105090516*x1/( 0.657731453039811*x1 + 0.0338737664203932*x2) + 2766.63/(222.65 + x3) - x5 =L= 11.1422900361581; e6.. x1 + x2 =E= 1; * set non-default bounds x1.lo = 1E-6; x1.up = 1; x2.lo = 1E-6; x2.up = 1; x3.lo = 40; x3.up = 90; * set non-default levels x1.l = 0.878; x2.l = 0.122; x3.l = 55.726; 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: 2024-08-26 Git hash: 6cc1607f