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Instance hhfair
Formatsⓘ | ams gms mod nl osil py |
Primal Bounds (infeas ≤ 1e-08)ⓘ | |
Other points (infeas > 1e-08)ⓘ | |
Dual Boundsⓘ | -87.15903761 (LINDO) |
Referencesⓘ | Fair, Ray C, Specification, Estimation, and Analysis of Macroeconomic Models, Harvard University Press, Cambridge, Mass, 1984. |
Sourceⓘ | GAMS Model Library model hhfair |
Applicationⓘ | Financial Optimization |
Added to libraryⓘ | 31 Jul 2001 |
Problem typeⓘ | NLP |
#Variablesⓘ | 29 |
#Binary Variablesⓘ | 0 |
#Integer Variablesⓘ | 0 |
#Nonlinear Variablesⓘ | 15 |
#Nonlinear Binary Variablesⓘ | 0 |
#Nonlinear Integer Variablesⓘ | 0 |
Objective Senseⓘ | min |
Objective typeⓘ | signomial |
Objective curvatureⓘ | indefinite |
#Nonzeros in Objectiveⓘ | 3 |
#Nonlinear Nonzeros in Objectiveⓘ | 3 |
#Constraintsⓘ | 25 |
#Linear Constraintsⓘ | 19 |
#Quadratic Constraintsⓘ | 3 |
#Polynomial Constraintsⓘ | 0 |
#Signomial Constraintsⓘ | 0 |
#General Nonlinear Constraintsⓘ | 3 |
Operands in Gen. Nonlin. Functionsⓘ | sqr vcpower |
Constraints curvatureⓘ | indefinite |
#Nonzeros in Jacobianⓘ | 77 |
#Nonlinear Nonzeros in Jacobianⓘ | 18 |
#Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 41 |
#Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 11 |
#Blocks in Hessian of Lagrangianⓘ | 4 |
Minimal blocksize in Hessian of Lagrangianⓘ | 3 |
Maximal blocksize in Hessian of Lagrangianⓘ | 4 |
Average blocksize in Hessian of Lagrangianⓘ | 3.75 |
#Semicontinuitiesⓘ | 0 |
#Nonlinear Semicontinuitiesⓘ | 0 |
#SOS type 1ⓘ | 0 |
#SOS type 2ⓘ | 0 |
Minimal coefficientⓘ | 1.0000e-02 |
Maximal coefficientⓘ | 1.0047e+03 |
Infeasibility of initial pointⓘ | 470 |
Sparsity Jacobianⓘ | |
Sparsity Hessian of Lagrangianⓘ |
$offlisting * * Equation counts * Total E G L N X C B * 26 20 3 3 0 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 30 30 0 0 0 0 0 0 * FX 2 * * Nonzero counts * Total const NL DLL * 81 60 21 0 * * Solve m using NLP minimizing objvar; Variables x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14,x15,x16,x17,objvar ,x19,x20,x21,x22,x23,x24,x25,x26,x27,x28,x29,x30; Equations e1,e2,e3,e4,e5,e6,e7,e8,e9,e10,e11,e12,e13,e14,e15,e16,e17,e18,e19 ,e20,e21,e22,e23,e24,e25,e26; e1.. -x26**0.944*x25*x27**0.891136 - objvar =E= 0; e2.. -0.01*sqr(0.5*x5**0.5 + 0.5*(1004.72366 - x8 - x15)**0.5) + x25 =E= 0; e3.. -0.01*sqr(0.5*x6**0.5 + 0.5*(1004.72366 - x9 - x16)**0.5) + x26 =E= 0; e4.. -0.01*sqr(0.5*x7**0.5 + 0.5*(1004.72366 - x10 - x17)**0.5) + x27 =E= 0; e5.. - 0.07*x2 - x8 + x28 =E= 0; e6.. - 0.07*x3 - x9 + x29 =E= 0; e7.. - 0.07*x4 - x10 + x30 =E= 0; e8.. x22 - 0.2*x28 =E= 0; e9.. x23 - 0.2*x29 =E= 0; e10.. x24 - 0.2*x30 =E= 0; e11.. x5 + x19 + x22 - x28 =E= 0; e12.. x6 + x20 + x23 - x29 =E= 0; e13.. x7 + x21 + x24 - x30 =E= 0; e14.. x1 - x2 + x11 - x12 + x19 =E= 0; e15.. x2 - x3 + x12 - x13 + x20 =E= 0; e16.. x3 - x4 + x13 - x14 + x21 =E= 0; e17.. x15*(x12 - 0.255905*x5) =E= 1; e18.. x16*(x13 - 0.255905*x6) =E= 1; e19.. x17*(x14 - 0.255905*x7) =E= 1; e20.. x4 + x14 =E= 1100; e21.. - 0.25846405*x5 + x12 =G= 0; e22.. - 0.25846405*x6 + x13 =G= 0; e23.. - 0.25846405*x7 + x14 =G= 0; e24.. x8 + x15 =L= 904.251294; e25.. x9 + x16 =L= 904.251294; e26.. x10 + x17 =L= 904.251294; * set non-default bounds x1.fx = 1000; x5.lo = 100; x6.lo = 100; x7.lo = 100; x8.lo = 100; x8.up = 400; x9.lo = 100; x9.up = 400; x10.lo = 100; x10.up = 400; x11.fx = 100; x25.lo = 0.01; x26.lo = 0.01; x27.lo = 0.01; * set non-default levels x2.l = 1000; x3.l = 1000; x4.l = 1000; x8.l = 400; x9.l = 400; x10.l = 400; x12.l = 100; x13.l = 100; x14.l = 100; x25.l = 1; x26.l = 1; x27.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;
Last updated: 2024-12-17 Git hash: 8eaceb91