MINLPLib
A Library of Mixed-Integer and Continuous Nonlinear Programming Instances
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Instance sssd22-08
Stochastic Service System Design. Servers are modeled as M/M/1 queues, and a set of customers must be assigned to the servers which can be operated at different service levels. The objective is to minimize assignment and operating costs.
| Formatsⓘ | ams gms mod nl osil py |
| Primal Bounds (infeas ≤ 1e-08)ⓘ | |
| Other points (infeas > 1e-08)ⓘ | |
| Dual Boundsⓘ | 508195.48490000 (ALPHAECP) 508625.50080000 (ANTIGONE) 508713.73050000 (BARON) 508385.28260000 (BONMIN) 152873.77100000 (COUENNE) 500693.55950000 (LINDO) 508713.71720000 (SCIP) 508583.01550000 (SHOT) |
| Referencesⓘ | Elhedhli, Samir, Service System Design with Immobile Servers, Stochastic Demand, and Congestion, Manufacturing & Service Operations Management, 8:1, 2006, 92-97. Günlük, Oktay and Linderoth, Jeff T, Perspective reformulations of mixed integer nonlinear programs with indicator variables, Mathematical Programming, 124:1-2, 2010, 183-205. Günlük, Oktay and Linderoth, Jeff T, Perspective Reformulation and Applications. In Lee, Jon and Leyffer, Sven, Eds, Mixed Integer Nonlinear Programming, Springer, 2012, 61-89. |
| Applicationⓘ | Service System Design |
| Added to libraryⓘ | 24 Feb 2014 |
| Problem typeⓘ | MBNLP |
| #Variablesⓘ | 232 |
| #Binary Variablesⓘ | 200 |
| #Integer Variablesⓘ | 0 |
| #Nonlinear Variablesⓘ | 8 |
| #Nonlinear Binary Variablesⓘ | 0 |
| #Nonlinear Integer Variablesⓘ | 0 |
| Objective Senseⓘ | min |
| Objective typeⓘ | linear |
| Objective curvatureⓘ | linear |
| #Nonzeros in Objectiveⓘ | 208 |
| #Nonlinear Nonzeros in Objectiveⓘ | 0 |
| #Constraintsⓘ | 86 |
| #Linear Constraintsⓘ | 62 |
| #Quadratic Constraintsⓘ | 0 |
| #Polynomial Constraintsⓘ | 0 |
| #Signomial Constraintsⓘ | 0 |
| #General Nonlinear Constraintsⓘ | 24 |
| Operands in Gen. Nonlin. Functionsⓘ | div |
| Constraints curvatureⓘ | convex |
| #Nonzeros in Jacobianⓘ | 496 |
| #Nonlinear Nonzeros in Jacobianⓘ | 24 |
| #Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 8 |
| #Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 8 |
| #Blocks in Hessian of Lagrangianⓘ | 8 |
| 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ⓘ | 5.1483e-01 |
| Maximal coefficientⓘ | 9.0114e+04 |
| Infeasibility of initial pointⓘ | 1 |
| Sparsity Jacobianⓘ |  |
| Sparsity Hessian of Lagrangianⓘ |  |
$offlisting
*
* Equation counts
* Total E G L N X C B
* 87 31 0 56 0 0 0 0
*
* Variable counts
* x b i s1s s2s sc si
* Total cont binary integer sos1 sos2 scont sint
* 233 33 200 0 0 0 0 0
* FX 0
*
* Nonzero counts
* Total const NL DLL
* 705 681 24 0
*
* Solve m using MINLP minimizing objvar;
Variables b1,b2,b3,b4,b5,b6,b7,b8,b9,b10,b11,b12,b13,b14,b15,b16,b17,b18,b19
,b20,b21,b22,b23,b24,b25,b26,b27,b28,b29,b30,b31,b32,b33,b34,b35,b36
,b37,b38,b39,b40,b41,b42,b43,b44,b45,b46,b47,b48,b49,b50,b51,b52,b53
,b54,b55,b56,b57,b58,b59,b60,b61,b62,b63,b64,b65,b66,b67,b68,b69,b70
,b71,b72,b73,b74,b75,b76,b77,b78,b79,b80,b81,b82,b83,b84,b85,b86,b87
,b88,b89,b90,b91,b92,b93,b94,b95,b96,b97,b98,b99,b100,b101,b102,b103
,b104,b105,b106,b107,b108,b109,b110,b111,b112,b113,b114,b115,b116
,b117,b118,b119,b120,b121,b122,b123,b124,b125,b126,b127,b128,b129
,b130,b131,b132,b133,b134,b135,b136,b137,b138,b139,b140,b141,b142
,b143,b144,b145,b146,b147,b148,b149,b150,b151,b152,b153,b154,b155
,b156,b157,b158,b159,b160,b161,b162,b163,b164,b165,b166,b167,b168
,b169,b170,b171,b172,b173,b174,b175,b176,b177,b178,b179,b180,b181
,b182,b183,b184,b185,b186,b187,b188,b189,b190,b191,b192,b193,b194
,b195,b196,b197,b198,b199,b200,x201,x202,x203,x204,x205,x206,x207
,x208,x209,x210,x211,x212,x213,x214,x215,x216,x217,x218,x219,x220
,x221,x222,x223,x224,x225,x226,x227,x228,x229,x230,x231,x232,objvar;
Positive Variables x201,x202,x203,x204,x205,x206,x207,x208,x209,x210,x211
,x212,x213,x214,x215,x216,x217,x218,x219,x220,x221,x222,x223,x224
,x225,x226,x227,x228,x229,x230,x231,x232;
Binary Variables b1,b2,b3,b4,b5,b6,b7,b8,b9,b10,b11,b12,b13,b14,b15,b16,b17
,b18,b19,b20,b21,b22,b23,b24,b25,b26,b27,b28,b29,b30,b31,b32,b33,b34
,b35,b36,b37,b38,b39,b40,b41,b42,b43,b44,b45,b46,b47,b48,b49,b50,b51
,b52,b53,b54,b55,b56,b57,b58,b59,b60,b61,b62,b63,b64,b65,b66,b67,b68
,b69,b70,b71,b72,b73,b74,b75,b76,b77,b78,b79,b80,b81,b82,b83,b84,b85
,b86,b87,b88,b89,b90,b91,b92,b93,b94,b95,b96,b97,b98,b99,b100,b101
,b102,b103,b104,b105,b106,b107,b108,b109,b110,b111,b112,b113,b114
,b115,b116,b117,b118,b119,b120,b121,b122,b123,b124,b125,b126,b127
,b128,b129,b130,b131,b132,b133,b134,b135,b136,b137,b138,b139,b140
,b141,b142,b143,b144,b145,b146,b147,b148,b149,b150,b151,b152,b153
,b154,b155,b156,b157,b158,b159,b160,b161,b162,b163,b164,b165,b166
,b167,b168,b169,b170,b171,b172,b173,b174,b175,b176,b177,b178,b179
,b180,b181,b182,b183,b184,b185,b186,b187,b188,b189,b190,b191,b192
,b193,b194,b195,b196,b197,b198,b199,b200;
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;
e1.. - 208.792389579557*b1 - 217.220995426524*b2 - 219.328963727163*b3
- 335.651755242039*b4 - 357.330454546574*b5 - 346.288650280159*b6
- 266.831359835122*b7 - 456.270698882756*b8 - 598.603823802659*b9
- 472.76096139298*b10 - 440.895090698712*b11 - 587.391445247834*b12
- 645.591064716537*b13 - 842.289923714761*b14 - 121.085274825763*b15
- 827.593258115164*b16 - 197.884040776939*b17 - 265.670270246372*b18
- 277.19406330985*b19 - 300.515348924627*b20 - 219.737117743978*b21
- 29.7605015712574*b22 - 340.166179406841*b23 - 283.856776912609*b24
- 530.371712601246*b25 - 666.342201226349*b26 - 688.262656274643*b27
- 749.884149250718*b28 - 433.188232823123*b29 - 179.889568973086*b30
- 781.513894249438*b31 - 721.578241933227*b32 - 385.365331428565*b33
- 397.310751547733*b34 - 394.709618384088*b35 - 488.796381342564*b36
- 69.1228046698849*b37 - 353.774426772291*b38 - 291.790884852353*b39
- 571.723273315939*b40 - 155.222386730589*b41 - 99.2899226882794*b42
- 86.2196187420574*b43 - 139.670924625187*b44 - 254.800918398364*b45
- 272.399716241454*b46 - 63.6669462920938*b47 - 233.124068769687*b48
- 420.433611725096*b49 - 392.743531304658*b50 - 381.78274307056*b51
- 492.339258879241*b52 - 221.765410784674*b53 - 471.509884685296*b54
- 198.32681114913*b55 - 616.946947175197*b56 - 367.630309121365*b57
- 460.597168454611*b58 - 476.106543114266*b59 - 507.291994932137*b60
- 326.794364462657*b61 - 129.791978899027*b62 - 548.796138386955*b63
- 473.395038736004*b64 - 325.447206766794*b65 - 490.469713344171*b66
- 523.815789714576*b67 - 505.034257474519*b68 - 692.411426088716*b69
- 200.55621733527*b70 - 775.7926466443*b71 - 384.953901158781*b72
- 90.6602362937041*b73 - 141.123442371391*b74 - 161.956213738203*b75
- 109.048636049605*b76 - 478.505506249041*b77 - 280.921006907188*b78
- 370.54186916052*b79 - 90.0885571257413*b80 - 298.187335183707*b81
- 446.806547302861*b82 - 478.682808405872*b83 - 442.741538849651*b84
- 691.38591250887*b85 - 245.191525741426*b86 - 733.088602836978*b87
- 307.319437419187*b88 - 337.888982918121*b89 - 419.167156191436*b90
- 433.274587404946*b91 - 450.445951605631*b92 - 325.562889404499*b93
- 140.625297509477*b94 - 505.752773889592*b95 - 406.547094311348*b96
- 222.184700988121*b97 - 240.706858859471*b98 - 241.574880311851*b99
- 291.369743048828*b100 - 15.2686323496579*b101 - 176.809772873193*b102
- 203.189667115456*b103 - 327.65591970594*b104 - 129.877228863824*b105
- 213.864055621011*b106 - 228.904588570087*b107 - 267.714721001121*b108
- 296.129922427254*b109 - 120.997544341877*b110 - 335.613750709585*b111
- 282.466658282013*b112 - 672.898864110698*b113 - 756.187216722396*b114
- 765.66484083818*b115 - 865.192465249929*b116 - 236.611873044182*b117
- 434.91997598185*b118 - 723.10739482889*b119 - 901.139517259906*b120
- 219.602048486048*b121 - 201.157387320931*b122 - 198.047001409938*b123
- 323.278842853872*b124 - 375.740471906088*b125 - 384.320011362398*b126
- 227.915246894889*b127 - 461.206035499698*b128 - 136.697588440332*b129
- 195.795672174039*b130 - 206.510139458451*b131 - 266.993643756477*b132
- 266.428828703525*b133 - 172.197876959554*b134 - 285.213773004863*b135
- 314.039353185424*b136 - 100.546799414253*b137 - 158.869600643741*b138
- 169.177101793017*b139 - 192.372362299551*b140 - 196.928390780027*b141
- 62.8591174163952*b142 - 238.906880310977*b143 - 194.625572987735*b144
- 426.229131856612*b145 - 514.495326782553*b146 - 528.382010861139*b147
- 570.004598026737*b148 - 306.963768408293*b149 - 192.514354981969*b150
- 576.445077629097*b151 - 547.274100083715*b152 - 355.78132876986*b153
- 441.081415856693*b154 - 455.950573614429*b155 - 472.925391866814*b156
- 345.902082835143*b157 - 150.24855415155*b158 - 533.120100629792*b159
- 425.427178535863*b160 - 312.501954887052*b161 - 342.776531219538*b162
- 344.744206407029*b163 - 420.060812382554*b164 - 52.4443211841249*b165
- 248.287530992381*b166 - 297.059157510037*b167 - 474.854530167614*b168
- 304.572783869897*b169 - 413.92096155854*b170 - 436.177554965223*b171
- 418.666286552571*b172 - 507.602151838219*b173 - 167.124705382621*b174
- 599.946283215143*b175 - 318.432467752406*b176 - 428.280624*b177
- 146.029695525341*b178 - 90.4403621070536*b179 - 443.1386765*b180
- 145.975961746562*b181 - 88.8621264293527*b182 - 397.34356925*b183
- 142.916859315786*b184 - 90.9090638831941*b185 - 292.49438275*b186
- 113.954644649109*b187 - 75.4405570646217*b188 - 444.36193375*b189
- 145.506402206668*b190 - 88.3118947061088*b191 - 277.65857175*b192
- 112.736894888761*b193 - 76.1920106860745*b194 - 477.617688*b195
- 153.675005321166*b196 - 92.4547040495498*b197 - 336.34625775*b198
- 118.939551077852*b199 - 75.017245954943*b200 - 90113.9517259906*x201
- 90113.9517259906*x202 - 90113.9517259906*x203 - 90113.9517259906*x204
- 90113.9517259906*x205 - 90113.9517259906*x206 - 90113.9517259906*x207
- 90113.9517259906*x208 + objvar =E= 0;
e2.. 1.171932132*b1 + 1.380580128*b9 + 0.642148796*b17 + 1.365957869*b25
+ 0.883196807*b33 + 0.529359847*b41 + 0.944441234*b49 + 0.877264007*b57
+ 1.377561448*b65 + 0.849949624*b73 + 1.272241722*b81 + 0.725429288*b89
+ 0.514827484*b97 + 0.859331887*b105 + 1.257166993*b113
+ 1.166831024*b121 + 0.873786249*b129 + 0.571003843*b137
+ 0.894706799*b145 + 0.757692826*b153 + 0.793024066*b161
+ 0.914251523*b169 - 2.1220404046875*x209 - 4.244080809375*x210
- 6.3661212140625*x211 =E= 0;
e3.. 1.171932132*b2 + 1.380580128*b10 + 0.642148796*b18 + 1.365957869*b26
+ 0.883196807*b34 + 0.529359847*b42 + 0.944441234*b50 + 0.877264007*b58
+ 1.377561448*b66 + 0.849949624*b74 + 1.272241722*b82 + 0.725429288*b90
+ 0.514827484*b98 + 0.859331887*b106 + 1.257166993*b114
+ 1.166831024*b122 + 0.873786249*b130 + 0.571003843*b138
+ 0.894706799*b146 + 0.757692826*b154 + 0.793024066*b162
+ 0.914251523*b170 - 1.9799363876875*x212 - 3.959872775375*x213
- 5.9398091630625*x214 =E= 0;
e4.. 1.171932132*b3 + 1.380580128*b11 + 0.642148796*b19 + 1.365957869*b27
+ 0.883196807*b35 + 0.529359847*b43 + 0.944441234*b51 + 0.877264007*b59
+ 1.377561448*b67 + 0.849949624*b75 + 1.272241722*b83 + 0.725429288*b91
+ 0.514827484*b99 + 0.859331887*b107 + 1.257166993*b115
+ 1.166831024*b123 + 0.873786249*b131 + 0.571003843*b139
+ 0.894706799*b147 + 0.757692826*b155 + 0.793024066*b163
+ 0.914251523*b171 - 2.31103048*x215 - 4.62206096*x216 - 6.93309144*x217
=E= 0;
e5.. 1.171932132*b4 + 1.380580128*b12 + 0.642148796*b20 + 1.365957869*b28
+ 0.883196807*b36 + 0.529359847*b44 + 0.944441234*b52 + 0.877264007*b60
+ 1.377561448*b68 + 0.849949624*b76 + 1.272241722*b84 + 0.725429288*b92
+ 0.514827484*b100 + 0.859331887*b108 + 1.257166993*b116
+ 1.166831024*b124 + 0.873786249*b132 + 0.571003843*b140
+ 0.894706799*b148 + 0.757692826*b156 + 0.793024066*b164
+ 0.914251523*b172 - 2.1619703510625*x218 - 4.323940702125*x219
- 6.4859110531875*x220 =E= 0;
e6.. 1.171932132*b5 + 1.380580128*b13 + 0.642148796*b21 + 1.365957869*b29
+ 0.883196807*b37 + 0.529359847*b45 + 0.944441234*b53 + 0.877264007*b61
+ 1.377561448*b69 + 0.849949624*b77 + 1.272241722*b85 + 0.725429288*b93
+ 0.514827484*b101 + 0.859331887*b109 + 1.257166993*b117
+ 1.166831024*b125 + 0.873786249*b133 + 0.571003843*b141
+ 0.894706799*b149 + 0.757692826*b157 + 0.793024066*b165
+ 0.914251523*b173 - 1.9501097226875*x221 - 3.900219445375*x222
- 5.8503291680625*x223 =E= 0;
e7.. 1.171932132*b6 + 1.380580128*b14 + 0.642148796*b22 + 1.365957869*b30
+ 0.883196807*b38 + 0.529359847*b46 + 0.944441234*b54 + 0.877264007*b62
+ 1.377561448*b70 + 0.849949624*b78 + 1.272241722*b86 + 0.725429288*b94
+ 0.514827484*b102 + 0.859331887*b110 + 1.257166993*b118
+ 1.166831024*b126 + 0.873786249*b134 + 0.571003843*b142
+ 0.894706799*b150 + 0.757692826*b158 + 0.793024066*b166
+ 0.914251523*b174 - 2.32308593*x224 - 4.64617186*x225 - 6.96925779*x226
=E= 0;
e8.. 1.171932132*b7 + 1.380580128*b15 + 0.642148796*b23 + 1.365957869*b31
+ 0.883196807*b39 + 0.529359847*b47 + 0.944441234*b55 + 0.877264007*b63
+ 1.377561448*b71 + 0.849949624*b79 + 1.272241722*b87 + 0.725429288*b95
+ 0.514827484*b103 + 0.859331887*b111 + 1.257166993*b119
+ 1.166831024*b127 + 0.873786249*b135 + 0.571003843*b143
+ 0.894706799*b151 + 0.757692826*b159 + 0.793024066*b167
+ 0.914251523*b175 - 1.9885435838125*x227 - 3.977087167625*x228
- 5.9656307514375*x229 =E= 0;
e9.. 1.171932132*b8 + 1.380580128*b16 + 0.642148796*b24 + 1.365957869*b32
+ 0.883196807*b40 + 0.529359847*b48 + 0.944441234*b56 + 0.877264007*b64
+ 1.377561448*b72 + 0.849949624*b80 + 1.272241722*b88 + 0.725429288*b96
+ 0.514827484*b104 + 0.859331887*b112 + 1.257166993*b120
+ 1.166831024*b128 + 0.873786249*b136 + 0.571003843*b144
+ 0.894706799*b152 + 0.757692826*b160 + 0.793024066*b168
+ 0.914251523*b176 - 1.8590587860625*x230 - 3.718117572125*x231
- 5.5771763581875*x232 =E= 0;
e10.. b1 + b2 + b3 + b4 + b5 + b6 + b7 + b8 =E= 1;
e11.. b9 + b10 + b11 + b12 + b13 + b14 + b15 + b16 =E= 1;
e12.. b17 + b18 + b19 + b20 + b21 + b22 + b23 + b24 =E= 1;
e13.. b25 + b26 + b27 + b28 + b29 + b30 + b31 + b32 =E= 1;
e14.. b33 + b34 + b35 + b36 + b37 + b38 + b39 + b40 =E= 1;
e15.. b41 + b42 + b43 + b44 + b45 + b46 + b47 + b48 =E= 1;
e16.. b49 + b50 + b51 + b52 + b53 + b54 + b55 + b56 =E= 1;
e17.. b57 + b58 + b59 + b60 + b61 + b62 + b63 + b64 =E= 1;
e18.. b65 + b66 + b67 + b68 + b69 + b70 + b71 + b72 =E= 1;
e19.. b73 + b74 + b75 + b76 + b77 + b78 + b79 + b80 =E= 1;
e20.. b81 + b82 + b83 + b84 + b85 + b86 + b87 + b88 =E= 1;
e21.. b89 + b90 + b91 + b92 + b93 + b94 + b95 + b96 =E= 1;
e22.. b97 + b98 + b99 + b100 + b101 + b102 + b103 + b104 =E= 1;
e23.. b105 + b106 + b107 + b108 + b109 + b110 + b111 + b112 =E= 1;
e24.. b113 + b114 + b115 + b116 + b117 + b118 + b119 + b120 =E= 1;
e25.. b121 + b122 + b123 + b124 + b125 + b126 + b127 + b128 =E= 1;
e26.. b129 + b130 + b131 + b132 + b133 + b134 + b135 + b136 =E= 1;
e27.. b137 + b138 + b139 + b140 + b141 + b142 + b143 + b144 =E= 1;
e28.. b145 + b146 + b147 + b148 + b149 + b150 + b151 + b152 =E= 1;
e29.. b153 + b154 + b155 + b156 + b157 + b158 + b159 + b160 =E= 1;
e30.. b161 + b162 + b163 + b164 + b165 + b166 + b167 + b168 =E= 1;
e31.. b169 + b170 + b171 + b172 + b173 + b174 + b175 + b176 =E= 1;
e32.. b177 + b178 + b179 =L= 1;
e33.. b180 + b181 + b182 =L= 1;
e34.. b183 + b184 + b185 =L= 1;
e35.. b186 + b187 + b188 =L= 1;
e36.. b189 + b190 + b191 =L= 1;
e37.. b192 + b193 + b194 =L= 1;
e38.. b195 + b196 + b197 =L= 1;
e39.. b198 + b199 + b200 =L= 1;
e40.. - b177 + x209 =L= 0;
e41.. - b178 + x210 =L= 0;
e42.. - b179 + x211 =L= 0;
e43.. - b180 + x212 =L= 0;
e44.. - b181 + x213 =L= 0;
e45.. - b182 + x214 =L= 0;
e46.. - b183 + x215 =L= 0;
e47.. - b184 + x216 =L= 0;
e48.. - b185 + x217 =L= 0;
e49.. - b186 + x218 =L= 0;
e50.. - b187 + x219 =L= 0;
e51.. - b188 + x220 =L= 0;
e52.. - b189 + x221 =L= 0;
e53.. - b190 + x222 =L= 0;
e54.. - b191 + x223 =L= 0;
e55.. - b192 + x224 =L= 0;
e56.. - b193 + x225 =L= 0;
e57.. - b194 + x226 =L= 0;
e58.. - b195 + x227 =L= 0;
e59.. - b196 + x228 =L= 0;
e60.. - b197 + x229 =L= 0;
e61.. - b198 + x230 =L= 0;
e62.. - b199 + x231 =L= 0;
e63.. - b200 + x232 =L= 0;
e64.. -x201/(1 + x201) + x209 =L= 0;
e65.. -x201/(1 + x201) + x210 =L= 0;
e66.. -x201/(1 + x201) + x211 =L= 0;
e67.. -x202/(1 + x202) + x212 =L= 0;
e68.. -x202/(1 + x202) + x213 =L= 0;
e69.. -x202/(1 + x202) + x214 =L= 0;
e70.. -x203/(1 + x203) + x215 =L= 0;
e71.. -x203/(1 + x203) + x216 =L= 0;
e72.. -x203/(1 + x203) + x217 =L= 0;
e73.. -x204/(1 + x204) + x218 =L= 0;
e74.. -x204/(1 + x204) + x219 =L= 0;
e75.. -x204/(1 + x204) + x220 =L= 0;
e76.. -x205/(1 + x205) + x221 =L= 0;
e77.. -x205/(1 + x205) + x222 =L= 0;
e78.. -x205/(1 + x205) + x223 =L= 0;
e79.. -x206/(1 + x206) + x224 =L= 0;
e80.. -x206/(1 + x206) + x225 =L= 0;
e81.. -x206/(1 + x206) + x226 =L= 0;
e82.. -x207/(1 + x207) + x227 =L= 0;
e83.. -x207/(1 + x207) + x228 =L= 0;
e84.. -x207/(1 + x207) + x229 =L= 0;
e85.. -x208/(1 + x208) + x230 =L= 0;
e86.. -x208/(1 + x208) + x231 =L= 0;
e87.. -x208/(1 + x208) + x232 =L= 0;
Model m / all /;
m.limrow=0; m.limcol=0;
m.tolproj=0.0;
$if NOT '%gams.u1%' == '' $include '%gams.u1%'
$if not set MINLP $set MINLP MINLP
Solve m using %MINLP% minimizing objvar;
Last updated: 2024-12-17 Git hash: 8eaceb91