MINLPLib
A Library of Mixed-Integer and Continuous Nonlinear Programming Instances
Home // Instances // Documentation // Download // Statistics
Instance least
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ⓘ | Bracken, Jerome and McCormick, Garth P, Chapter 8.4. In Bracken, Jerome and McCormick, Garth P, Selected Applications of Nonlinear Programming, John Wiley and Sons, New York, 1968, 89-90. |
Sourceⓘ | GAMS Model Library model least |
Applicationⓘ | Statistics |
Added to libraryⓘ | 31 Jul 2001 |
Problem typeⓘ | NLP |
#Variablesⓘ | 3 |
#Binary Variablesⓘ | 0 |
#Integer Variablesⓘ | 0 |
#Nonlinear Variablesⓘ | 3 |
#Nonlinear Binary Variablesⓘ | 0 |
#Nonlinear Integer Variablesⓘ | 0 |
Objective Senseⓘ | min |
Objective typeⓘ | nonlinear |
Objective curvatureⓘ | indefinite |
#Nonzeros in Objectiveⓘ | 3 |
#Nonlinear Nonzeros in Objectiveⓘ | 3 |
#Constraintsⓘ | 0 |
#Linear Constraintsⓘ | 0 |
#Quadratic Constraintsⓘ | 0 |
#Polynomial Constraintsⓘ | 0 |
#Signomial Constraintsⓘ | 0 |
#General Nonlinear Constraintsⓘ | 0 |
Operands in Gen. Nonlin. Functionsⓘ | exp mul sqr |
Constraints curvatureⓘ | linear |
#Nonzeros in Jacobianⓘ | 0 |
#Nonlinear Nonzeros in Jacobianⓘ | 0 |
#Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 9 |
#Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 3 |
#Blocks in Hessian of Lagrangianⓘ | 1 |
Minimal blocksize in Hessian of Lagrangianⓘ | 3 |
Maximal blocksize in Hessian of Lagrangianⓘ | 3 |
Average blocksize in Hessian of Lagrangianⓘ | 3.0 |
#Semicontinuitiesⓘ | 0 |
#Nonlinear Semicontinuitiesⓘ | 0 |
#SOS type 1ⓘ | 0 |
#SOS type 2ⓘ | 0 |
Minimal coefficientⓘ | 3.0000e+00 |
Maximal coefficientⓘ | 4.6000e+02 |
Infeasibility of initial pointⓘ | 0 |
Sparsity Jacobianⓘ | |
Sparsity Hessian of Lagrangianⓘ |
$offlisting * * Equation counts * Total E G L N X C B * 1 1 0 0 0 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 4 4 0 0 0 0 0 0 * FX 0 * * Nonzero counts * Total const NL DLL * 4 1 3 0 * * Solve m using NLP minimizing objvar; Variables objvar,x2,x3,x4; Equations e1; e1.. -(sqr(127 - exp(-5*x4)*x3 - x2) + sqr(151 - exp(-3*x4)*x3 - x2) + sqr(379 - exp(-x4)*x3 - x2) + sqr(421 - exp(5*x4)*x3 - x2) + sqr(460 - exp(3*x4)* x3 - x2) + sqr(426 - exp(x4)*x3 - x2)) + objvar =E= 0; * set non-default bounds x4.lo = -5; x4.up = 5; * set non-default levels x2.l = 500; x3.l = -150; x4.l = -0.2; 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