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Instance ex8_4_3
Formatsⓘ | ams gms mod nl osil py |
Primal Bounds (infeas ≤ 1e-08)ⓘ | |
Other points (infeas > 1e-08)ⓘ | |
Dual Boundsⓘ | 0.00464606 (ANTIGONE) 0.00464962 (BARON) 0.00464972 (COUENNE) 0.00464972 (LINDO) 0.00464781 (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. Esposito, W R and Floudas, C A, Global Optimization in Parameter Estimation of Nonlinear Algebraic Models via the Error-in-Variables Approach, Industrial and Engineering Chemistry Research, 37:5, 1998, 1841-1858. Tjoa, I B and Biegler, L T, Reduced Successive Quadratic Programming Strategy for Errors-in-Variables Estimation, Computers and Chemical Engineering, 16:6, 1992, 523-533. Rod, V and Hancil, V, Iterative Estimation of Model Parameters When Measurements of All Variables are Subject to Error, Computers and Chemical Engineering, 4:2, 1980, 33-38. |
Sourceⓘ | Test Problem ex8.4.3 of Chapter 8 of Floudas e.a. handbook |
Added to libraryⓘ | 31 Jul 2001 |
Problem typeⓘ | NLP |
#Variablesⓘ | 52 |
#Binary Variablesⓘ | 0 |
#Integer Variablesⓘ | 0 |
#Nonlinear Variablesⓘ | 51 |
#Nonlinear Binary Variablesⓘ | 0 |
#Nonlinear Integer Variablesⓘ | 0 |
Objective Senseⓘ | min |
Objective typeⓘ | quadratic |
Objective curvatureⓘ | convex |
#Nonzeros in Objectiveⓘ | 50 |
#Nonlinear Nonzeros in Objectiveⓘ | 50 |
#Constraintsⓘ | 25 |
#Linear Constraintsⓘ | 0 |
#Quadratic Constraintsⓘ | 0 |
#Polynomial Constraintsⓘ | 0 |
#Signomial Constraintsⓘ | 0 |
#General Nonlinear Constraintsⓘ | 25 |
Operands in Gen. Nonlin. Functionsⓘ | div |
Constraints curvatureⓘ | indefinite |
#Nonzeros in Jacobianⓘ | 100 |
#Nonlinear Nonzeros in Jacobianⓘ | 50 |
#Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 101 |
#Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 51 |
#Blocks in Hessian of Lagrangianⓘ | 26 |
Minimal blocksize in Hessian of Lagrangianⓘ | 1 |
Maximal blocksize in Hessian of Lagrangianⓘ | 26 |
Average blocksize in Hessian of Lagrangianⓘ | 1.961538 |
#Semicontinuitiesⓘ | 0 |
#Nonlinear Semicontinuitiesⓘ | 0 |
#SOS type 1ⓘ | 0 |
#SOS type 2ⓘ | 0 |
Minimal coefficientⓘ | 1.1300e-01 |
Maximal coefficientⓘ | 1.8540e+00 |
Infeasibility of initial pointⓘ | 5.447 |
Sparsity Jacobianⓘ | |
Sparsity Hessian of Lagrangianⓘ |
$offlisting * * Equation counts * Total E G L N X C B * 26 26 0 0 0 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 53 53 0 0 0 0 0 0 * FX 0 * * Nonzero counts * Total const NL DLL * 151 51 100 0 * * Solve m using NLP minimizing objvar; Variables x1,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,x38,x39,x40,x41,x42,x43,x44,x45,x46,x47,x48,x49,x50,x51,x52 ,objvar; 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; e1.. -(sqr((-0.113) + x1) + sqr((-1.851) + x2) + sqr((-0.126) + x3) + sqr((- 1.854) + x4) + sqr((-0.172) + x5) + sqr((-1.849) + x6) + sqr((-0.155) + x7 ) + sqr((-1.815) + x8) + sqr((-0.219) + x9) + sqr((-1.828) + x10) + sqr((- 0.245) + x11) + sqr((-1.847) + x12) + sqr((-0.274) + x13) + sqr((-1.804) + x14) + sqr((-0.264) + x15) + sqr((-1.832) + x16) + sqr((-0.312) + x17) + sqr((-1.838) + x18) + sqr((-0.324) + x19) + sqr((-1.817) + x20) + sqr(( -0.333) + x21) + sqr((-1.82) + x22) + sqr((-0.399) + x23) + sqr((-1.845) + x24) + sqr((-0.417) + x25) + sqr((-1.829) + x26) + sqr((-0.419) + x27) + sqr((-1.832) + x28) + sqr((-0.439) + x29) + sqr((-1.82) + x30) + sqr((- 0.475) + x31) + sqr((-1.82) + x32) + sqr((-0.506) + x33) + sqr((-1.799) + x34) + sqr((-0.538) + x35) + sqr((-1.838) + x36) + sqr((-0.538) + x37) + sqr((-1.835) + x38) + sqr((-0.591) + x39) + sqr((-1.811) + x40) + sqr((- 0.578) + x41) + sqr((-1.794) + x42) + sqr((-0.626) + x43) + sqr((-1.825) + x44) + sqr((-0.659) + x45) + sqr((-1.801) + x46) + sqr((-0.668) + x47) + sqr((-1.81) + x48) + sqr((-0.687) + x49) + sqr((-1.802) + x50)) + objvar =E= 0; e2.. 1/(x1 - x52) - x2 + x51 =E= 0; e3.. 1/(x3 - x52) - x4 + x51 =E= 0; e4.. 1/(x5 - x52) - x6 + x51 =E= 0; e5.. 1/(x7 - x52) - x8 + x51 =E= 0; e6.. 1/(x9 - x52) - x10 + x51 =E= 0; e7.. 1/(x11 - x52) - x12 + x51 =E= 0; e8.. 1/(x13 - x52) - x14 + x51 =E= 0; e9.. 1/(x15 - x52) - x16 + x51 =E= 0; e10.. 1/(x17 - x52) - x18 + x51 =E= 0; e11.. 1/(x19 - x52) - x20 + x51 =E= 0; e12.. 1/(x21 - x52) - x22 + x51 =E= 0; e13.. 1/(x23 - x52) - x24 + x51 =E= 0; e14.. 1/(x25 - x52) - x26 + x51 =E= 0; e15.. 1/(x27 - x52) - x28 + x51 =E= 0; e16.. 1/(x29 - x52) - x30 + x51 =E= 0; e17.. 1/(x31 - x52) - x32 + x51 =E= 0; e18.. 1/(x33 - x52) - x34 + x51 =E= 0; e19.. 1/(x35 - x52) - x36 + x51 =E= 0; e20.. 1/(x37 - x52) - x38 + x51 =E= 0; e21.. 1/(x39 - x52) - x40 + x51 =E= 0; e22.. 1/(x41 - x52) - x42 + x51 =E= 0; e23.. 1/(x43 - x52) - x44 + x51 =E= 0; e24.. 1/(x45 - x52) - x46 + x51 =E= 0; e25.. 1/(x47 - x52) - x48 + x51 =E= 0; e26.. 1/(x49 - x52) - x50 + x51 =E= 0; * set non-default bounds x1.lo = -0.387; x1.up = 0.613; x2.lo = 1.351; x2.up = 2.351; x3.lo = -0.374; x3.up = 0.626; x4.lo = 1.354; x4.up = 2.354; x5.lo = -0.328; x5.up = 0.672; x6.lo = 1.349; x6.up = 2.349; x7.lo = -0.345; x7.up = 0.655; x8.lo = 1.315; x8.up = 2.315; x9.lo = -0.281; x9.up = 0.719; x10.lo = 1.328; x10.up = 2.328; x11.lo = -0.255; x11.up = 0.745; x12.lo = 1.347; x12.up = 2.347; x13.lo = -0.226; x13.up = 0.774; x14.lo = 1.304; x14.up = 2.304; x15.lo = -0.236; x15.up = 0.764; x16.lo = 1.332; x16.up = 2.332; x17.lo = -0.188; x17.up = 0.812; x18.lo = 1.338; x18.up = 2.338; x19.lo = -0.176; x19.up = 0.824; x20.lo = 1.317; x20.up = 2.317; x21.lo = -0.167; x21.up = 0.833; x22.lo = 1.32; x22.up = 2.32; x23.lo = -0.101; x23.up = 0.899; x24.lo = 1.345; x24.up = 2.345; x25.lo = -0.083; x25.up = 0.917; x26.lo = 1.329; x26.up = 2.329; x27.lo = -0.081; x27.up = 0.919; x28.lo = 1.332; x28.up = 2.332; x29.lo = -0.061; x29.up = 0.939; x30.lo = 1.32; x30.up = 2.32; x31.lo = -0.025; x31.up = 0.975; x32.lo = 1.32; x32.up = 2.32; x33.lo = 0.00600000000000001; x33.up = 1.006; x34.lo = 1.299; x34.up = 2.299; x35.lo = 0.038; x35.up = 1.038; x36.lo = 1.338; x36.up = 2.338; x37.lo = 0.038; x37.up = 1.038; x38.lo = 1.335; x38.up = 2.335; x39.lo = 0.091; x39.up = 1.091; x40.lo = 1.311; x40.up = 2.311; x41.lo = 0.078; x41.up = 1.078; x42.lo = 1.294; x42.up = 2.294; x43.lo = 0.126; x43.up = 1.126; x44.lo = 1.325; x44.up = 2.325; x45.lo = 0.159; x45.up = 1.159; x46.lo = 1.301; x46.up = 2.301; x47.lo = 0.168; x47.up = 1.168; x48.lo = 1.31; x48.up = 2.31; x49.lo = 0.187; x49.up = 1.187; x50.lo = 1.302; x50.up = 2.302; x51.lo = 1; x51.up = 10; x52.lo = 2; x52.up = 10; * set non-default levels x1.l = -0.215252868; x2.l = 2.194266708; x3.l = 0.176375356; x4.l = 1.655137904; x5.l = -0.035787883; x6.l = 1.573052867; x7.l = 0.00483050400000007; x8.l = 2.171270347; x9.l = -0.213886277; x10.l = 1.828210669; x11.l = 0.743117627; x12.l = 1.925733378; x13.l = 0.765133039; x14.l = 2.066250467; x15.l = -0.105307517; x16.l = 1.971718759; x17.l = -0.028482136; x18.l = 1.588080533; x19.l = 0.492928609; x20.l = 1.752356381; x21.l = 0.192700266; x22.l = 1.671441368; x23.l = 0.03049159; x24.l = 1.495101788; x25.l = 0.50611365; x26.l = 2.159892812; x27.l = 0.149815738; x28.l = 1.99773446; x29.l = 0.714857606; x30.l = 1.623658477; x31.l = 0.085492291; x32.l = 1.822384866; x33.l = 0.166172762; x34.l = 2.171462311; x35.l = 0.303114545; x36.l = 1.623814322; x37.l = 0.631955922; x38.l = 2.057719071; x39.l = 0.719248677; x40.l = 1.774797865; x41.l = 0.491306994; x42.l = 1.411695357; x43.l = 0.440212267; x44.l = 1.371551514; x45.l = 0.497550272; x46.l = 1.483099593; x47.l = 0.813727127; x48.l = 1.870745547; x49.l = 0.95696172; x50.l = 1.599805864; x51.l = 6.949956349; x52.l = 8.046573392; 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