MINLPLib
A Library of Mixed-Integer and Continuous Nonlinear Programming Instances
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Instance oaer
Formatsⓘ | ams gms mod nl osil py |
Primal Bounds (infeas ≤ 1e-08)ⓘ | |
Other points (infeas > 1e-08)ⓘ | |
Dual Boundsⓘ | -1.92309929 (ANTIGONE) -1.92309852 (BARON) -1.92309851 (COUENNE) -1.92310000 (LINDO) -1.92309852 (SCIP) -1.92309902 (SHOT) |
Referencesⓘ | Floudas, C A, Nonlinear and Mixed Integer Optimization: Fundamentals and Applications, Oxford University Press, 1995. |
Sourceⓘ | MINOPT Model Library model oaer_test.dat |
Added to libraryⓘ | 01 May 2001 |
Problem typeⓘ | MBNLP |
#Variablesⓘ | 9 |
#Binary Variablesⓘ | 3 |
#Integer Variablesⓘ | 0 |
#Nonlinear Variablesⓘ | 2 |
#Nonlinear Binary Variablesⓘ | 0 |
#Nonlinear Integer Variablesⓘ | 0 |
Objective Senseⓘ | min |
Objective typeⓘ | linear |
Objective curvatureⓘ | linear |
#Nonzeros in Objectiveⓘ | 9 |
#Nonlinear Nonzeros in Objectiveⓘ | 0 |
#Constraintsⓘ | 7 |
#Linear Constraintsⓘ | 5 |
#Quadratic Constraintsⓘ | 0 |
#Polynomial Constraintsⓘ | 0 |
#Signomial Constraintsⓘ | 0 |
#General Nonlinear Constraintsⓘ | 2 |
Operands in Gen. Nonlin. Functionsⓘ | log |
Constraints curvatureⓘ | indefinite |
#Nonzeros in Jacobianⓘ | 16 |
#Nonlinear Nonzeros in Jacobianⓘ | 2 |
#Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 2 |
#Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 2 |
#Blocks in Hessian of Lagrangianⓘ | 2 |
Minimal blocksize in Hessian of Lagrangianⓘ | 1 |
Maximal blocksize in Hessian of Lagrangianⓘ | 1 |
Average blocksize in Hessian of Lagrangianⓘ | 1.0 |
#Semicontinuitiesⓘ | 0 |
#Nonlinear Semicontinuitiesⓘ | 0 |
#SOS type 1ⓘ | 0 |
#SOS type 2ⓘ | 0 |
Minimal coefficientⓘ | 9.0000e-01 |
Maximal coefficientⓘ | 1.1000e+01 |
Infeasibility of initial pointⓘ | 0 |
Sparsity Jacobianⓘ | |
Sparsity Hessian of Lagrangianⓘ |
$offlisting * * Equation counts * Total E G L N X C B * 8 4 0 4 0 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 10 7 3 0 0 0 0 0 * FX 0 * * Nonzero counts * Total const NL DLL * 26 24 2 0 * * Solve m using MINLP minimizing objvar; Variables x1,x2,x3,x4,x5,x6,b7,b8,b9,objvar; Positive Variables x1,x2,x3,x4,x5,x6; Binary Variables b7,b8,b9; Equations e1,e2,e3,e4,e5,e6,e7,e8; e1.. - 1.8*x1 - 1.8*x2 - 7*x3 - x4 - 1.2*x5 + 11*x6 - 3.5*b7 - b8 - 1.5*b9 + objvar =E= 0; e2.. -log(1 + x1) + x4 =E= 0; e3.. -1.2*log(1 + x2) + x5 =E= 0; e4.. - 0.9*x3 - 0.9*x4 - 0.9*x5 + x6 =E= 0; e5.. x6 - b7 =L= 0; e6.. x4 - 1.111111*b8 =L= 0; e7.. x5 - 1.111111*b9 =L= 0; e8.. b8 + b9 =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 MINLP $set MINLP MINLP Solve m using %MINLP% minimizing objvar;
Last updated: 2024-08-26 Git hash: 6cc1607f