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Instance kriging_peaks-full050
Gaussian process regression for the peaks functions using 50 datapoints. This is the full-space formulation where intermediate variables are defined by additional constraints.
| Formatsⓘ | ams gms mod nl osil py |
| Primal Bounds (infeas ≤ 1e-08)ⓘ | |
| Other points (infeas > 1e-08)ⓘ | |
| Dual Boundsⓘ | -1.32073930 (ANTIGONE) -1.15659634 (BARON) -1.15659922 (GUROBI) -1.15658991 (LINDO) -1.15660050 (SCIP) |
| Referencesⓘ | Schweidtmann, Artur M., Bongartz, Dominik, Grothe, Daniel, Kerkenhoff, Tim, Lin, Xiaopeng, Najman, Jaromil, and Mitsos, Alexander, Deterministic global optimization with Gaussian processes embedded, Mathematical Programming Computation, 13:3, 2021, 553-581. |
| Applicationⓘ | Kriging |
| Added to libraryⓘ | 11 Dec 2020 |
| Problem typeⓘ | NLP |
| #Variablesⓘ | 106 |
| #Binary Variablesⓘ | 0 |
| #Integer Variablesⓘ | 0 |
| #Nonlinear Variablesⓘ | 52 |
| #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ⓘ | 104 |
| #Linear Constraintsⓘ | 4 |
| #Quadratic Constraintsⓘ | 50 |
| #Polynomial Constraintsⓘ | 0 |
| #Signomial Constraintsⓘ | 0 |
| #General Nonlinear Constraintsⓘ | 50 |
| Operands in Gen. Nonlin. Functionsⓘ | exp mul sqrt |
| Constraints curvatureⓘ | indefinite |
| #Nonzeros in Jacobianⓘ | 307 |
| #Nonlinear Nonzeros in Jacobianⓘ | 150 |
| #Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 52 |
| #Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 52 |
| #Blocks in Hessian of Lagrangianⓘ | 52 |
| Minimal blocksize in Hessian of Lagrangianⓘ | 1 |
| Maximal blocksize in Hessian of Lagrangianⓘ | 1 |
| Average blocksize in Hessian of Lagrangianⓘ | 1.0 |
| #Semicontinuitiesⓘ | 0 |
| #Nonlinear Semicontinuitiesⓘ | 0 |
| #SOS type 1ⓘ | 0 |
| #SOS type 2ⓘ | 0 |
| Minimal coefficientⓘ | 4.9484e-04 |
| Maximal coefficientⓘ | 6.3938e+01 |
| Infeasibility of initial pointⓘ | 65.41 |
| Sparsity Jacobianⓘ |  |
| Sparsity Hessian of Lagrangianⓘ |  |
$offlisting
*
* Equation counts
* Total E G L N X C B
* 105 105 0 0 0 0 0 0
*
* Variable counts
* x b i s1s s2s sc si
* Total cont binary integer sos1 sos2 scont sint
* 107 107 0 0 0 0 0 0
* FX 0
*
* Nonzero counts
* Total const NL DLL
* 309 159 150 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,x53
,x54,x55,x56,x57,x58,x59,x60,x61,x62,x63,x64,x65,x66,x67,x68,x69,x70
,x71,x72,x73,x74,x75,x76,x77,x78,x79,x80,x81,x82,x83,x84,x85,x86,x87
,x88,x89,x90,x91,x92,x93,x94,x95,x96,x97,x98,x99,x100,x101,x102,x103
,x104,x105,x106,objvar;
Positive Variables 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,x53,x54
,x55,x56,x57,x58,x59,x60,x61,x62,x63,x64,x65,x66,x67,x68,x69,x70,x71
,x72,x73,x74,x75,x76,x77,x78,x79,x80,x81,x82,x83,x84,x85,x86,x87,x88
,x89,x90,x91,x92,x93,x94,x95,x96,x97,x98,x99,x100,x101,x102,x103
,x104;
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,e36
,e37,e38,e39,e40,e41,e42,e43,e44,e45,e46,e47,e48,e49,e50,e51,e52,e53
,e54,e55,e56,e57,e58,e59,e60,e61,e62,e63,e64,e65,e66,e67,e68,e69,e70
,e71,e72,e73,e74,e75,e76,e77,e78,e79,e80,e81,e82,e83,e84,e85,e86,e87
,e88,e89,e90,e91,e92,e93,e94,e95,e96,e97,e98,e99,e100,e101,e102,e103
,e104,e105;
e1.. - x106 + objvar =E= 0;
e2.. 0.166666666666667*x1 - x3 =E= -0.5;
e3.. 0.166666666666667*x2 - x4 =E= -0.5;
e4.. 63.938104949048*sqr(0.91444408088704 - x3) + 11.9516380997938*sqr(
0.999827877577323 - x4) - x5 =E= 0;
e5.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x5) + 1.66666666666667*x5)*
exp(-2.23606797749979*sqrt(x5)) - x6 =E= 0;
e6.. 63.938104949048*sqr(0.512270639538623 - x3) + 11.9516380997938*sqr(
0.341832211664162 - x4) - x7 =E= 0;
e7.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x7) + 1.66666666666667*x7)*
exp(-2.23606797749979*sqrt(x7)) - x8 =E= 0;
e8.. 63.938104949048*sqr(0.828588651321815 - x3) + 11.9516380997938*sqr(
0.922821824461503 - x4) - x9 =E= 0;
e9.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x9) + 1.66666666666667*x9)*
exp(-2.23606797749979*sqrt(x9)) - x10 =E= 0;
e10.. 63.938104949048*sqr(0.196070004978241 - x3) + 11.9516380997938*sqr(
0.258795790737015 - x4) - x11 =E= 0;
e11.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x11) + 1.66666666666667*x11)
*exp(-2.23606797749979*sqrt(x11)) - x12 =E= 0;
e12.. 63.938104949048*sqr(0.925574140459005 - x3) + 11.9516380997938*sqr(
0.759134777875101 - x4) - x13 =E= 0;
e13.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x13) + 1.66666666666667*x13)
*exp(-2.23606797749979*sqrt(x13)) - x14 =E= 0;
e14.. 63.938104949048*sqr(0.544706424830881 - x3) + 11.9516380997938*sqr(
0.0714978839191896 - x4) - x15 =E= 0;
e15.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x15) + 1.66666666666667*x15)
*exp(-2.23606797749979*sqrt(x15)) - x16 =E= 0;
e16.. 63.938104949048*sqr(0.648362902134195 - x3) + 11.9516380997938*sqr(
0.199809710635483 - x4) - x17 =E= 0;
e17.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x17) + 1.66666666666667*x17)
*exp(-2.23606797749979*sqrt(x17)) - x18 =E= 0;
e18.. 63.938104949048*sqr(0.893120932447526 - x3) + 11.9516380997938*sqr(
0.767134170090178 - x4) - x19 =E= 0;
e19.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x19) + 1.66666666666667*x19)
*exp(-2.23606797749979*sqrt(x19)) - x20 =E= 0;
e20.. 63.938104949048*sqr(0.779840229982808 - x3) + 11.9516380997938*sqr(
0.115228373952418 - x4) - x21 =E= 0;
e21.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x21) + 1.66666666666667*x21)
*exp(-2.23606797749979*sqrt(x21)) - x22 =E= 0;
e22.. 63.938104949048*sqr(0.980244861711599 - x3) + 11.9516380997938*sqr(
0.232896066498765 - x4) - x23 =E= 0;
e23.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x23) + 1.66666666666667*x23)
*exp(-2.23606797749979*sqrt(x23)) - x24 =E= 0;
e24.. 63.938104949048*sqr(0.171423093396044 - x3) + 11.9516380997938*sqr(
0.479648256287106 - x4) - x25 =E= 0;
e25.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x25) + 1.66666666666667*x25)
*exp(-2.23606797749979*sqrt(x25)) - x26 =E= 0;
e26.. 63.938104949048*sqr(0.0442328283704769 - x3) + 11.9516380997938*sqr(
0.646012035209209 - x4) - x27 =E= 0;
e27.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x27) + 1.66666666666667*x27)
*exp(-2.23606797749979*sqrt(x27)) - x28 =E= 0;
e28.. 63.938104949048*sqr(0.691411127164531 - x3) + 11.9516380997938*sqr(
0.949521423561418 - x4) - x29 =E= 0;
e29.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x29) + 1.66666666666667*x29)
*exp(-2.23606797749979*sqrt(x29)) - x30 =E= 0;
e30.. 63.938104949048*sqr(0.307339086280815 - x3) + 11.9516380997938*sqr(
0.823718436988909 - x4) - x31 =E= 0;
e31.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x31) + 1.66666666666667*x31)
*exp(-2.23606797749979*sqrt(x31)) - x32 =E= 0;
e32.. 63.938104949048*sqr(0.156987059593039 - x3) + 11.9516380997938*sqr(
0.704190234776601 - x4) - x33 =E= 0;
e33.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x33) + 1.66666666666667*x33)
*exp(-2.23606797749979*sqrt(x33)) - x34 =E= 0;
e34.. 63.938104949048*sqr(0.714276281917298 - x3) + 11.9516380997938*sqr(
0.787100183039457 - x4) - x35 =E= 0;
e35.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x35) + 1.66666666666667*x35)
*exp(-2.23606797749979*sqrt(x35)) - x36 =E= 0;
e36.. 63.938104949048*sqr(0.367402952149829 - x3) + 11.9516380997938*sqr(
0.0395596030436262 - x4) - x37 =E= 0;
e37.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x37) + 1.66666666666667*x37)
*exp(-2.23606797749979*sqrt(x37)) - x38 =E= 0;
e38.. 63.938104949048*sqr(0.587231126187775 - x3) + 11.9516380997938*sqr(
0.579245001413374 - x4) - x39 =E= 0;
e39.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x39) + 1.66666666666667*x39)
*exp(-2.23606797749979*sqrt(x39)) - x40 =E= 0;
e40.. 63.938104949048*sqr(0.329488378583342 - x3) + 11.9516380997938*sqr(
0.888756970308057 - x4) - x41 =E= 0;
e41.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x41) + 1.66666666666667*x41)
*exp(-2.23606797749979*sqrt(x41)) - x42 =E= 0;
e42.. 63.938104949048*sqr(0.426454462097756 - x3) + 11.9516380997938*sqr(
0.442589666022276 - x4) - x43 =E= 0;
e43.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x43) + 1.66666666666667*x43)
*exp(-2.23606797749979*sqrt(x43)) - x44 =E= 0;
e44.. 63.938104949048*sqr(0.618294064225034 - x3) + 11.9516380997938*sqr(
0.00770431754139585 - x4) - x45 =E= 0;
e45.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x45) + 1.66666666666667*x45)
*exp(-2.23606797749979*sqrt(x45)) - x46 =E= 0;
e46.. 63.938104949048*sqr(0.287839839566682 - x3) + 11.9516380997938*sqr(
0.144827186434541 - x4) - x47 =E= 0;
e47.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x47) + 1.66666666666667*x47)
*exp(-2.23606797749979*sqrt(x47)) - x48 =E= 0;
e48.. 63.938104949048*sqr(0.568950032842984 - x3) + 11.9516380997938*sqr(
0.604419102860498 - x4) - x49 =E= 0;
e49.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x49) + 1.66666666666667*x49)
*exp(-2.23606797749979*sqrt(x49)) - x50 =E= 0;
e50.. 63.938104949048*sqr(0.404869181965135 - x3) + 11.9516380997938*sqr(
0.660090190214415 - x4) - x51 =E= 0;
e51.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x51) + 1.66666666666667*x51)
*exp(-2.23606797749979*sqrt(x51)) - x52 =E= 0;
e52.. 63.938104949048*sqr(0.872708180136192 - x3) + 11.9516380997938*sqr(
0.632747129594836 - x4) - x53 =E= 0;
e53.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x53) + 1.66666666666667*x53)
*exp(-2.23606797749979*sqrt(x53)) - x54 =E= 0;
e54.. 63.938104949048*sqr(0.968711755891586 - x3) + 11.9516380997938*sqr(
0.318643122915592 - x4) - x55 =E= 0;
e55.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x55) + 1.66666666666667*x55)
*exp(-2.23606797749979*sqrt(x55)) - x56 =E= 0;
e56.. 63.938104949048*sqr(0.460753668532643 - x3) + 11.9516380997938*sqr(
0.539244831501377 - x4) - x57 =E= 0;
e57.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x57) + 1.66666666666667*x57)
*exp(-2.23606797749979*sqrt(x57)) - x58 =E= 0;
e58.. 63.938104949048*sqr(0.72652385482879 - x3) + 11.9516380997938*sqr(
0.816356936855873 - x4) - x59 =E= 0;
e59.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x59) + 1.66666666666667*x59)
*exp(-2.23606797749979*sqrt(x59)) - x60 =E= 0;
e60.. 63.938104949048*sqr(0.957248446547711 - x3) + 11.9516380997938*sqr(
0.408207398550875 - x4) - x61 =E= 0;
e61.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x61) + 1.66666666666667*x61)
*exp(-2.23606797749979*sqrt(x61)) - x62 =E= 0;
e62.. 63.938104949048*sqr(0.794750682614849 - x3) + 11.9516380997938*sqr(
0.084497120889644 - x4) - x63 =E= 0;
e63.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x63) + 1.66666666666667*x63)
*exp(-2.23606797749979*sqrt(x63)) - x64 =E= 0;
e64.. 63.938104949048*sqr(0.227847372253769 - x3) + 11.9516380997938*sqr(
0.681203760209944 - x4) - x65 =E= 0;
e65.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x65) + 1.66666666666667*x65)
*exp(-2.23606797749979*sqrt(x65)) - x66 =E= 0;
e66.. 63.938104949048*sqr(0.672167890972669 - x3) + 11.9516380997938*sqr(
0.908892360525134 - x4) - x67 =E= 0;
e67.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x67) + 1.66666666666667*x67)
*exp(-2.23606797749979*sqrt(x67)) - x68 =E= 0;
e68.. 63.938104949048*sqr(0.389240322657806 - x3) + 11.9516380997938*sqr(
0.855065265920299 - x4) - x69 =E= 0;
e69.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x69) + 1.66666666666667*x69)
*exp(-2.23606797749979*sqrt(x69)) - x70 =E= 0;
e70.. 63.938104949048*sqr(0.250419824463881 - x3) + 11.9516380997938*sqr(
0.123958515062189 - x4) - x71 =E= 0;
e71.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x71) + 1.66666666666667*x71)
*exp(-2.23606797749979*sqrt(x71)) - x72 =E= 0;
e72.. 63.938104949048*sqr(0.751338884270706 - x3) + 11.9516380997938*sqr(
0.168231540605081 - x4) - x73 =E= 0;
e73.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x73) + 1.66666666666667*x73)
*exp(-2.23606797749979*sqrt(x73)) - x74 =E= 0;
e74.. 63.938104949048*sqr(0.442625854866514 - x3) + 11.9516380997938*sqr(
0.485359903912025 - x4) - x75 =E= 0;
e75.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x75) + 1.66666666666667*x75)
*exp(-2.23606797749979*sqrt(x75)) - x76 =E= 0;
e76.. 63.938104949048*sqr(0.630060774132016 - x3) + 11.9516380997938*sqr(
0.865973040158068 - x4) - x77 =E= 0;
e77.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x77) + 1.66666666666667*x77)
*exp(-2.23606797749979*sqrt(x77)) - x78 =E= 0;
e78.. 63.938104949048*sqr(0.201567418081754 - x3) + 11.9516380997938*sqr(
0.0541844010231221 - x4) - x79 =E= 0;
e79.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x79) + 1.66666666666667*x79)
*exp(-2.23606797749979*sqrt(x79)) - x80 =E= 0;
e80.. 63.938104949048*sqr(0.0688002798156933 - x3) + 11.9516380997938*sqr(
0.729069908135606 - x4) - x81 =E= 0;
e81.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x81) + 1.66666666666667*x81)
*exp(-2.23606797749979*sqrt(x81)) - x82 =E= 0;
e82.. 63.938104949048*sqr(0.525665882763195 - x3) + 11.9516380997938*sqr(
0.293372576581166 - x4) - x83 =E= 0;
e83.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x83) + 1.66666666666667*x83)
*exp(-2.23606797749979*sqrt(x83)) - x84 =E= 0;
e84.. 63.938104949048*sqr(0.814666152229046 - x3) + 11.9516380997938*sqr(
0.439994250606541 - x4) - x85 =E= 0;
e85.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x85) + 1.66666666666667*x85)
*exp(-2.23606797749979*sqrt(x85)) - x86 =E= 0;
e86.. 63.938104949048*sqr(0.000494837260784549 - x3) + 11.9516380997938*sqr(
0.329105652324109 - x4) - x87 =E= 0;
e87.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x87) + 1.66666666666667*x87)
*exp(-2.23606797749979*sqrt(x87)) - x88 =E= 0;
e88.. 63.938104949048*sqr(0.346107221824958 - x3) + 11.9516380997938*sqr(
0.399699261152344 - x4) - x89 =E= 0;
e89.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x89) + 1.66666666666667*x89)
*exp(-2.23606797749979*sqrt(x89)) - x90 =E= 0;
e90.. 63.938104949048*sqr(0.116587170646063 - x3) + 11.9516380997938*sqr(
0.584598585997641 - x4) - x91 =E= 0;
e91.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x91) + 1.66666666666667*x91)
*exp(-2.23606797749979*sqrt(x91)) - x92 =E= 0;
e92.. 63.938104949048*sqr(0.0981435670313116 - x3) + 11.9516380997938*sqr(
0.203823777512949 - x4) - x93 =E= 0;
e93.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x93) + 1.66666666666667*x93)
*exp(-2.23606797749979*sqrt(x93)) - x94 =E= 0;
e94.. 63.938104949048*sqr(0.484116247882851 - x3) + 11.9516380997938*sqr(
0.968040087195413 - x4) - x95 =E= 0;
e95.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x95) + 1.66666666666667*x95)
*exp(-2.23606797749979*sqrt(x95)) - x96 =E= 0;
e96.. 63.938104949048*sqr(0.0258195777506217 - x3) + 11.9516380997938*sqr(
0.364843552111112 - x4) - x97 =E= 0;
e97.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x97) + 1.66666666666667*x97)
*exp(-2.23606797749979*sqrt(x97)) - x98 =E= 0;
e98.. 63.938104949048*sqr(0.847199435240466 - x3) + 11.9516380997938*sqr(
0.514365810567645 - x4) - x99 =E= 0;
e99.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x99) + 1.66666666666667*x99)
*exp(-2.23606797749979*sqrt(x99)) - x100 =E= 0;
e100.. 63.938104949048*sqr(0.278722256637232 - x3) + 11.9516380997938*sqr(
0.270454503788408 - x4) - x101 =E= 0;
e101.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x101) + 1.66666666666667*
x101)*exp(-2.23606797749979*sqrt(x101)) - x102 =E= 0;
e102.. 63.938104949048*sqr(0.129959773843819 - x3) + 11.9516380997938*sqr(
0.558945606997871 - x4) - x103 =E= 0;
e103.. 0.415803483145436*(1 + 2.23606797749979*sqrt(x103) + 1.66666666666667*
x103)*exp(-2.23606797749979*sqrt(x103)) - x104 =E= 0;
e104.. - 0.123076996278144*x6 - 0.166421086062989*x8 - 0.247803126196198*x10
+ 0.102086768548506*x12 - 0.152070272173613*x14 - 0.31796162836734*x16
- 1.74464626473608*x18 - 0.173141983185604*x20 - 0.0253715466673997*x22
- 0.132028059968171*x24 - 0.858588122349194*x26
+ 0.0240133726821279*x28 - 0.391385083608166*x30
+ 0.445633363954121*x32 - 0.0491516256763154*x34
+ 0.645620041306043*x36 - 0.179138859785582*x38
+ 0.0488906047534055*x40 - 0.0607138296143051*x42
+ 1.59105001805531*x44 + 0.388963397056983*x46 - 0.254558018663405*x48
+ 0.00421538096394381*x50 + 0.469095859503578*x52
- 0.0621621438235275*x54 - 0.138495991869403*x56
- 0.0182879338983809*x58 + 0.263948780641845*x60
- 0.133915556636388*x62 - 0.00545727925585648*x64
- 0.612349070958348*x66 - 0.0885690213152005*x68 + 1.24538427696921*x70
- 0.100410048120177*x72 - 0.18814890123585*x74 + 0.806971033783215*x76
+ 1.00895893257056*x78 - 0.0590064161050039*x80
+ 0.0388998578796231*x82 - 2.69806306452684*x84 + 0.840699249061092*x86
- 0.0377634067064712*x88 + 0.622118304461606*x90
- 0.150694157880986*x92 + 0.0185321439616882*x94
- 0.264551856159385*x96 + 0.000749397135734776*x98
+ 0.417930913778528*x100 + 0.155111489695813*x102
- 0.30231026780197*x104 - x105 =E= 0;
e105.. 1.28655551917808*x105 - x106 =E= -0.270964000255915;
* set non-default bounds
x1.lo = -3; x1.up = 3;
x2.lo = -3; x2.up = 3;
x3.lo = -1; x3.up = 1;
x4.lo = -1; x4.up = 1;
x5.up = 10000000;
x6.up = 10000000;
x7.up = 10000000;
x8.up = 10000000;
x9.up = 10000000;
x10.up = 10000000;
x11.up = 10000000;
x12.up = 10000000;
x13.up = 10000000;
x14.up = 10000000;
x15.up = 10000000;
x16.up = 10000000;
x17.up = 10000000;
x18.up = 10000000;
x19.up = 10000000;
x20.up = 10000000;
x21.up = 10000000;
x22.up = 10000000;
x23.up = 10000000;
x24.up = 10000000;
x25.up = 10000000;
x26.up = 10000000;
x27.up = 10000000;
x28.up = 10000000;
x29.up = 10000000;
x30.up = 10000000;
x31.up = 10000000;
x32.up = 10000000;
x33.up = 10000000;
x34.up = 10000000;
x35.up = 10000000;
x36.up = 10000000;
x37.up = 10000000;
x38.up = 10000000;
x39.up = 10000000;
x40.up = 10000000;
x41.up = 10000000;
x42.up = 10000000;
x43.up = 10000000;
x44.up = 10000000;
x45.up = 10000000;
x46.up = 10000000;
x47.up = 10000000;
x48.up = 10000000;
x49.up = 10000000;
x50.up = 10000000;
x51.up = 10000000;
x52.up = 10000000;
x53.up = 10000000;
x54.up = 10000000;
x55.up = 10000000;
x56.up = 10000000;
x57.up = 10000000;
x58.up = 10000000;
x59.up = 10000000;
x60.up = 10000000;
x61.up = 10000000;
x62.up = 10000000;
x63.up = 10000000;
x64.up = 10000000;
x65.up = 10000000;
x66.up = 10000000;
x67.up = 10000000;
x68.up = 10000000;
x69.up = 10000000;
x70.up = 10000000;
x71.up = 10000000;
x72.up = 10000000;
x73.up = 10000000;
x74.up = 10000000;
x75.up = 10000000;
x76.up = 10000000;
x77.up = 10000000;
x78.up = 10000000;
x79.up = 10000000;
x80.up = 10000000;
x81.up = 10000000;
x82.up = 10000000;
x83.up = 10000000;
x84.up = 10000000;
x85.up = 10000000;
x86.up = 10000000;
x87.up = 10000000;
x88.up = 10000000;
x89.up = 10000000;
x90.up = 10000000;
x91.up = 10000000;
x92.up = 10000000;
x93.up = 10000000;
x94.up = 10000000;
x95.up = 10000000;
x96.up = 10000000;
x97.up = 10000000;
x98.up = 10000000;
x99.up = 10000000;
x100.up = 10000000;
x101.up = 10000000;
x102.up = 10000000;
x103.up = 10000000;
x104.up = 10000000;
x105.lo = -10000000; x105.up = 10000000;
x106.lo = -10000000; x106.up = 10000000;
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