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A Library of Mixed-Integer and Continuous Nonlinear Programming Instances
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Instance ex14_1_7
| 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. Ratschek, H and Rokne, J, Experiments using interval analysis for solving a circuit design problem, Journal of Global Optimization, 3:4, 1993, 501-518. |
| Sourceⓘ | Test Problem ex14.1.7 of Chapter 14 of Floudas e.a. handbook |
| Added to libraryⓘ | 31 Jul 2001 |
| Problem typeⓘ | NLP |
| #Variablesⓘ | 10 |
| #Binary Variablesⓘ | 0 |
| #Integer Variablesⓘ | 0 |
| #Nonlinear Variablesⓘ | 9 |
| #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ⓘ | 17 |
| #Linear Constraintsⓘ | 0 |
| #Quadratic Constraintsⓘ | 1 |
| #Polynomial Constraintsⓘ | 0 |
| #Signomial Constraintsⓘ | 0 |
| #General Nonlinear Constraintsⓘ | 16 |
| Operands in Gen. Nonlin. Functionsⓘ | exp mul |
| Constraints curvatureⓘ | indefinite |
| #Nonzeros in Jacobianⓘ | 116 |
| #Nonlinear Nonzeros in Jacobianⓘ | 100 |
| #Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 59 |
| #Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 5 |
| #Blocks in Hessian of Lagrangianⓘ | 1 |
| Minimal blocksize in Hessian of Lagrangianⓘ | 9 |
| Maximal blocksize in Hessian of Lagrangianⓘ | 9 |
| Average blocksize in Hessian of Lagrangianⓘ | 9.0 |
| #Semicontinuitiesⓘ | 0 |
| #Nonlinear Semicontinuitiesⓘ | 0 |
| #SOS type 1ⓘ | 0 |
| #SOS type 2ⓘ | 0 |
| Minimal coefficientⓘ | 5.2095e-03 |
| Maximal coefficientⓘ | 2.1148e+02 |
| Infeasibility of initial pointⓘ | 211.5 |
| Sparsity Jacobianⓘ | ![]() |
| Sparsity Hessian of Lagrangianⓘ | ![]() |
$offlisting
*
* Equation counts
* Total E G L N X C B
* 18 2 0 16 0 0 0 0
*
* Variable counts
* x b i s1s s2s sc si
* Total cont binary integer sos1 sos2 scont sint
* 11 11 0 0 0 0 0 0
* FX 0
*
* Nonzero counts
* Total const NL DLL
* 118 18 100 0
*
* Solve m using NLP minimizing objvar;
Variables x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,objvar;
Positive Variables x1,x2,x3,x4,x5,x6,x7,x8,x9;
Equations e1,e2,e3,e4,e5,e6,e7,e8,e9,e10,e11,e12,e13,e14,e15,e16,e17,e18;
e1.. - x10 + objvar =E= 0;
e2.. (1 - x1*x2)*x3*(-1 + exp(x5*(0.485 - 0.0052095*x7 - 0.0285132*x8))) +
23.3037*x2 - x10 =L= 28.5132;
e3.. (1 - x1*x2)*x3*(-1 + exp(x5*(0.752 - 0.0100677*x7 - 0.1118467*x8))) +
101.779*x2 - x10 =L= 111.8467;
e4.. (1 - x1*x2)*x3*(-1 + exp(x5*(0.869 - 0.0229274*x7 - 0.1343884*x8))) +
111.461*x2 - x10 =L= 134.3884;
e5.. (1 - x1*x2)*x3*(-1 + exp(x5*(0.982 - 0.0202153*x7 - 0.2114823*x8))) +
191.267*x2 - x10 =L= 211.4823;
e6.. (-(1 - x1*x2)*x3*(-1 + exp(x5*(0.485 - 0.0052095*x7 - 0.0285132*x8)))) -
23.3037*x2 - x10 =L= -28.5132;
e7.. (-(1 - x1*x2)*x3*(-1 + exp(x5*(0.752 - 0.0100677*x7 - 0.1118467*x8)))) -
101.779*x2 - x10 =L= -111.8467;
e8.. (-(1 - x1*x2)*x3*(-1 + exp(x5*(0.869 - 0.0229274*x7 - 0.1343884*x8)))) -
111.461*x2 - x10 =L= -134.3884;
e9.. (-(1 - x1*x2)*x3*(-1 + exp(x5*(0.982 - 0.0202153*x7 - 0.2114823*x8)))) -
191.267*x2 - x10 =L= -211.4823;
e10.. (1 - x1*x2)*x4*(-1 + exp(x6*(0.116 - 0.0052095*x7 + 0.0233037*x9))) -
28.5132*x1 - x10 =L= -23.3037;
e11.. (1 - x1*x2)*x4*(-1 + exp(x6*(-0.502 - 0.0100677*x7 + 0.101779*x9))) -
111.8467*x1 - x10 =L= -101.779;
e12.. (1 - x1*x2)*x4*(-1 + exp(x6*(0.166 - 0.0229274*x7 + 0.111461*x9))) -
134.3884*x1 - x10 =L= -111.461;
e13.. (1 - x1*x2)*x4*(-1 + exp(x6*(-0.473 - 0.0202153*x7 + 0.191267*x9))) -
211.4823*x1 - x10 =L= -191.267;
e14.. 28.5132*x1 - (1 - x1*x2)*x4*(-1 + exp(x6*(0.116 - 0.0052095*x7 +
0.0233037*x9))) - x10 =L= 23.3037;
e15.. 111.8467*x1 - (1 - x1*x2)*x4*(-1 + exp(x6*(-0.502 - 0.0100677*x7 +
0.101779*x9))) - x10 =L= 101.779;
e16.. 134.3884*x1 - (1 - x1*x2)*x4*(-1 + exp(x6*(0.166 - 0.0229274*x7 +
0.111461*x9))) - x10 =L= 111.461;
e17.. 211.4823*x1 - (1 - x1*x2)*x4*(-1 + exp(x6*(-0.473 - 0.0202153*x7 +
0.191267*x9))) - x10 =L= 191.267;
e18.. x1*x3 - x2*x4 =E= 0;
* set non-default bounds
x1.up = 10;
x2.up = 10;
x3.up = 10;
x4.up = 10;
x5.up = 10;
x6.up = 10;
x7.up = 10;
x8.up = 10;
x9.up = 10;
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: 2025-08-07 Git hash: e62cedfc

