MINLPLib
A Library of Mixed-Integer and Continuous Nonlinear Programming Instances
Home // Instances // Documentation // Download // Statistics
Instance pooling_foulds2pq
PQ formulation of pooling problem. Explicitly added RLT constraints were removed from the original formulation of Alfaki and Haugland.
Formatsⓘ | ams gms lp mod nl osil pip py |
Primal Bounds (infeas ≤ 1e-08)ⓘ | |
Other points (infeas > 1e-08)ⓘ | |
Dual Boundsⓘ | -1100.00000100 (ANTIGONE) -1100.00000000 (BARON) -1100.00000000 (COUENNE) -1100.00000000 (GUROBI) -1100.00000000 (LINDO) -1100.00000000 (SCIP) |
Referencesⓘ | Foulds, L. R., Haugland, D., and Jörnsten, K., A bilinear approach to the pooling problem, Optimization, 24:1-2, 1992, 165-180. Alfaki, Mohammed and Haugland, Dag, Strong formulations for the pooling problem, Journal of Global Optimization, 56:3, 2013, 897-916. |
Sourceⓘ | Foulds2.gms from Standard Pooling Problem Instances |
Applicationⓘ | Pooling problem |
Added to libraryⓘ | 12 Sep 2017 |
Problem typeⓘ | QCP |
#Variablesⓘ | 36 |
#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ⓘ | 23 |
#Nonlinear Nonzeros in Objectiveⓘ | 0 |
#Constraintsⓘ | 34 |
#Linear Constraintsⓘ | 18 |
#Quadratic Constraintsⓘ | 16 |
#Polynomial Constraintsⓘ | 0 |
#Signomial Constraintsⓘ | 0 |
#General Nonlinear Constraintsⓘ | 0 |
Operands in Gen. Nonlin. Functionsⓘ | |
Constraints curvatureⓘ | indefinite |
#Nonzeros in Jacobianⓘ | 136 |
#Nonlinear Nonzeros in Jacobianⓘ | 32 |
#Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 32 |
#Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 0 |
#Blocks in Hessian of Lagrangianⓘ | 2 |
Minimal blocksize in Hessian of Lagrangianⓘ | 6 |
Maximal blocksize in Hessian of Lagrangianⓘ | 6 |
Average blocksize in Hessian of Lagrangianⓘ | 6.0 |
#Semicontinuitiesⓘ | 0 |
#Nonlinear Semicontinuitiesⓘ | 0 |
#SOS type 1ⓘ | 0 |
#SOS type 2ⓘ | 0 |
Minimal coefficientⓘ | 5.0000e-01 |
Maximal coefficientⓘ | 1.2000e+01 |
Infeasibility of initial pointⓘ | 1 |
Sparsity Jacobianⓘ | |
Sparsity Hessian of Lagrangianⓘ |
$offlisting * * Equation counts * Total E G L N X C B * 35 19 0 16 0 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 37 37 0 0 0 0 0 0 * FX 0 * * Nonzero counts * Total const NL DLL * 160 128 32 0 * * Solve m using NLP minimizing objvar; Variables objvar,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14,x15,x16,x17,x18 ,x19,x20,x21,x22,x23,x24,x25,x26,x27,x28,x29,x30,x31,x32,x33,x34,x35 ,x36,x37; Positive Variables x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14,x15,x16,x17 ,x18,x19,x20,x21,x22,x23,x24,x25,x26,x27,x28,x29,x30,x31,x32,x33,x34 ,x35,x36,x37; Equations e1,e2,e3,e4,e5,e6,e7,e8,e9,e10,e11,e12,e13,e14,e15,e16,e17,e18,e19 ,e20,e21,e22,e23,e24,e25,e26,e27,e28,e29,e30,e31,e32,e33,e34,e35; e1.. objvar - x6 + 5*x7 - 4*x8 + 2*x9 + 2*x10 + 8*x11 - x12 + 5*x13 + 3*x22 + 9*x23 + 6*x25 - 7*x26 - x27 - 10*x28 - 4*x29 + 6*x30 + 12*x31 + 3*x32 + 9*x33 - 4*x34 + 2*x35 - 7*x36 - x37 =E= 0; e2.. x22 + x23 + x24 + x25 =L= 600; e3.. x26 + x27 + x28 + x29 =L= 600; e4.. x6 + x7 + x8 + x9 =L= 600; e5.. x30 + x31 + x32 + x33 =L= 600; e6.. x34 + x35 + x36 + x37 =L= 600; e7.. x10 + x11 + x12 + x13 =L= 600; e8.. x22 + x23 + x24 + x25 + x26 + x27 + x28 + x29 =L= 600; e9.. x30 + x31 + x32 + x33 + x34 + x35 + x36 + x37 =L= 600; e10.. x6 + x10 + x22 + x26 + x30 + x34 =L= 100; e11.. x7 + x11 + x23 + x27 + x31 + x35 =L= 200; e12.. x8 + x12 + x24 + x28 + x32 + x36 =L= 100; e13.. x9 + x13 + x25 + x29 + x33 + x37 =L= 200; e14.. - 0.5*x6 + 0.5*x22 - 1.5*x26 + x30 - x34 =L= 0; e15.. 0.5*x7 + x11 + 1.5*x23 - 0.5*x27 + 2*x31 =L= 0; e16.. - x8 - 0.5*x12 - 2*x28 + 0.5*x32 - 1.5*x36 =L= 0; e17.. 0.5*x13 + x25 - x29 + 1.5*x33 - 0.5*x37 =L= 0; e18.. x2 + x3 =E= 1; e19.. x4 + x5 =E= 1; e20.. -x2*x14 + x22 =E= 0; e21.. -x2*x15 + x23 =E= 0; e22.. -x2*x16 + x24 =E= 0; e23.. -x2*x17 + x25 =E= 0; e24.. -x3*x14 + x26 =E= 0; e25.. -x3*x15 + x27 =E= 0; e26.. -x3*x16 + x28 =E= 0; e27.. -x3*x17 + x29 =E= 0; e28.. -x4*x18 + x30 =E= 0; e29.. -x4*x19 + x31 =E= 0; e30.. -x4*x20 + x32 =E= 0; e31.. -x4*x21 + x33 =E= 0; e32.. -x5*x18 + x34 =E= 0; e33.. -x5*x19 + x35 =E= 0; e34.. -x5*x20 + x36 =E= 0; e35.. -x5*x21 + x37 =E= 0; * set non-default bounds x2.up = 1; x3.up = 1; x4.up = 1; x5.up = 1; x6.up = 100; x7.up = 200; x8.up = 100; x9.up = 200; x10.up = 100; x11.up = 200; x12.up = 100; x13.up = 200; x14.up = 100; x15.up = 200; x16.up = 100; x17.up = 200; x18.up = 100; x19.up = 200; x20.up = 100; x21.up = 200; x22.up = 100; x23.up = 200; x24.up = 100; x25.up = 200; x26.up = 100; x27.up = 200; x28.up = 100; x29.up = 200; x30.up = 100; x31.up = 200; x32.up = 100; x33.up = 200; x34.up = 100; x35.up = 200; x36.up = 100; x37.up = 200; 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