MINLPLib
A Library of Mixed-Integer and Continuous Nonlinear Programming Instances
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Instance mhw4d
Formatsⓘ | ams gms mod nl osil pip py |
Primal Bounds (infeas ≤ 1e-08)ⓘ | |
Other points (infeas > 1e-08)ⓘ | |
Dual Boundsⓘ | 0.02931083 (COUENNE) 0.02931083 (LINDO) 0.02930981 (SCIP) |
Referencesⓘ | Wright, M H, Numerical Methods for Nonlinearly Constraint Optimization, PhD thesis, Stanford University, 1976. |
Sourceⓘ | GAMS Model Library model mhw4d |
Applicationⓘ | Test Problem |
Added to libraryⓘ | 31 Jul 2001 |
Problem typeⓘ | NLP |
#Variablesⓘ | 5 |
#Binary Variablesⓘ | 0 |
#Integer Variablesⓘ | 0 |
#Nonlinear Variablesⓘ | 5 |
#Nonlinear Binary Variablesⓘ | 0 |
#Nonlinear Integer Variablesⓘ | 0 |
Objective Senseⓘ | min |
Objective typeⓘ | polynomial |
Objective curvatureⓘ | indefinite |
#Nonzeros in Objectiveⓘ | 5 |
#Nonlinear Nonzeros in Objectiveⓘ | 5 |
#Constraintsⓘ | 3 |
#Linear Constraintsⓘ | 0 |
#Quadratic Constraintsⓘ | 2 |
#Polynomial Constraintsⓘ | 1 |
#Signomial Constraintsⓘ | 0 |
#General Nonlinear Constraintsⓘ | 0 |
Operands in Gen. Nonlin. Functionsⓘ | |
Constraints curvatureⓘ | indefinite |
#Nonzeros in Jacobianⓘ | 8 |
#Nonlinear Nonzeros in Jacobianⓘ | 5 |
#Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 15 |
#Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 5 |
#Blocks in Hessian of Lagrangianⓘ | 1 |
Minimal blocksize in Hessian of Lagrangianⓘ | 5 |
Maximal blocksize in Hessian of Lagrangianⓘ | 5 |
Average blocksize in Hessian of Lagrangianⓘ | 5.0 |
#Semicontinuitiesⓘ | 0 |
#Nonlinear Semicontinuitiesⓘ | 0 |
#SOS type 1ⓘ | 0 |
#SOS type 2ⓘ | 0 |
Minimal coefficientⓘ | 1.0000e+00 |
Maximal coefficientⓘ | 4.0000e+00 |
Infeasibility of initial pointⓘ | 2.243 |
Sparsity Jacobianⓘ | |
Sparsity Hessian of Lagrangianⓘ |
$offlisting * * Equation counts * Total E G L N X C B * 4 4 0 0 0 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 6 6 0 0 0 0 0 0 * FX 0 * * Nonzero counts * Total const NL DLL * 14 4 10 0 * * Solve m using NLP minimizing objvar; Variables objvar,x2,x3,x4,x5,x6; Equations e1,e2,e3,e4; e1.. -(sqr((-1) + x2) + sqr(x2 - x3) + POWER(x3 - x4,3) + POWER(x4 - x5,4) + POWER(x5 - x6,4)) + objvar =E= 0; e2.. sqr(x3) + POWER(x4,3) + x2 =E= 6.24264068711929; e3.. -sqr(x4) + x3 + x5 =E= 0.82842712474619; e4.. x2*x6 =E= 2; * set non-default levels x2.l = -1; x3.l = 2; x4.l = 1; x5.l = -2; x6.l = -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