MINLPLib
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Instance himmel16
Formatsⓘ | ams gms lp mod nl osil pip py |
Primal Bounds (infeas ≤ 1e-08)ⓘ | |
Other points (infeas > 1e-08)ⓘ | |
Dual Boundsⓘ | -0.86602541 (ANTIGONE) -0.86602550 (BARON) -0.86602540 (COUENNE) -0.86602687 (GUROBI) -0.86602540 (LINDO) -0.86602547 (SCIP) |
Referencesⓘ | Himmelblau, D M, Problem Number 16. In Himmelblau, D M, Applied Nonlinear Programming, Mc Graw Hill, New York, 1972. |
Sourceⓘ | GAMS Model Library model himmel16 |
Applicationⓘ | Geometry |
Added to libraryⓘ | 31 Jul 2001 |
Problem typeⓘ | QCP |
#Variablesⓘ | 18 |
#Binary Variablesⓘ | 0 |
#Integer Variablesⓘ | 0 |
#Nonlinear Variablesⓘ | 12 |
#Nonlinear Binary Variablesⓘ | 0 |
#Nonlinear Integer Variablesⓘ | 0 |
Objective Senseⓘ | min |
Objective typeⓘ | linear |
Objective curvatureⓘ | linear |
#Nonzeros in Objectiveⓘ | 6 |
#Nonlinear Nonzeros in Objectiveⓘ | 0 |
#Constraintsⓘ | 21 |
#Linear Constraintsⓘ | 0 |
#Quadratic Constraintsⓘ | 21 |
#Polynomial Constraintsⓘ | 0 |
#Signomial Constraintsⓘ | 0 |
#General Nonlinear Constraintsⓘ | 0 |
Operands in Gen. Nonlin. Functionsⓘ | |
Constraints curvatureⓘ | indefinite |
#Nonzeros in Jacobianⓘ | 90 |
#Nonlinear Nonzeros in Jacobianⓘ | 84 |
#Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 96 |
#Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 12 |
#Blocks in Hessian of Lagrangianⓘ | 1 |
Minimal blocksize in Hessian of Lagrangianⓘ | 12 |
Maximal blocksize in Hessian of Lagrangianⓘ | 12 |
Average blocksize in Hessian of Lagrangianⓘ | 12.0 |
#Semicontinuitiesⓘ | 0 |
#Nonlinear Semicontinuitiesⓘ | 0 |
#SOS type 1ⓘ | 0 |
#SOS type 2ⓘ | 0 |
Minimal coefficientⓘ | 5.0000e-01 |
Maximal coefficientⓘ | 1.0000e+00 |
Infeasibility of initial pointⓘ | 0.2 |
Sparsity Jacobianⓘ | |
Sparsity Hessian of Lagrangianⓘ |
$offlisting * * Equation counts * Total E G L N X C B * 22 7 0 15 0 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 19 19 0 0 0 0 0 0 * FX 3 * * Nonzero counts * Total const NL DLL * 97 13 84 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,x18 ,objvar; Equations e1,e2,e3,e4,e5,e6,e7,e8,e9,e10,e11,e12,e13,e14,e15,e16,e17,e18,e19 ,e20,e21,e22; e1.. sqr(x1 - x2) + sqr(x7 - x8) =L= 1; e2.. sqr(x1 - x3) + sqr(x7 - x9) =L= 1; e3.. sqr(x1 - x4) + sqr(x7 - x10) =L= 1; e4.. sqr(x1 - x5) + sqr(x7 - x11) =L= 1; e5.. sqr(x1 - x6) + sqr(x7 - x12) =L= 1; e6.. sqr(x2 - x3) + sqr(x8 - x9) =L= 1; e7.. sqr(x2 - x4) + sqr(x8 - x10) =L= 1; e8.. sqr(x2 - x5) + sqr(x8 - x11) =L= 1; e9.. sqr(x2 - x6) + sqr(x8 - x12) =L= 1; e10.. sqr(x3 - x4) + sqr(x9 - x10) =L= 1; e11.. sqr(x3 - x5) + sqr(x9 - x11) =L= 1; e12.. sqr(x3 - x6) + sqr(x9 - x12) =L= 1; e13.. sqr(x4 - x5) + sqr(x10 - x11) =L= 1; e14.. sqr(x4 - x6) + sqr(x10 - x12) =L= 1; e15.. sqr(x5 - x6) + sqr(x11 - x12) =L= 1; e16.. - x13 - x14 - x15 - x16 - x17 - x18 - objvar =E= 0; e17.. -0.5*(x1*x8 - x7*x2) + x13 =E= 0; e18.. -0.5*(x2*x9 - x8*x3) + x14 =E= 0; e19.. -0.5*(x3*x10 - x9*x4) + x15 =E= 0; e20.. -0.5*(x4*x11 - x10*x5) + x16 =E= 0; e21.. -0.5*(x5*x12 - x11*x6) + x17 =E= 0; e22.. -0.5*(x6*x7 - x12*x1) + x18 =E= 0; * set non-default bounds x1.fx = 0; x7.fx = 0; x8.fx = 0; * set non-default levels x2.l = 0.5; x3.l = 0.5; x4.l = 0.5; x9.l = 0.4; x10.l = 0.8; x11.l = 0.8; x12.l = 0.4; 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