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Instance p_ball_10b_5p_4d_m
Select 5-points in 4-dimensional balls, such that the l1-distance between all points is minimized. Only one point can be assigned to each ball, and in total there are 10 balls with radius one. This is a big-M formulation.
| Formatsⓘ | ams gms lp mod nl osil pip py |
| Primal Bounds (infeas ≤ 1e-08)ⓘ | |
| Other points (infeas > 1e-08)ⓘ | |
| Dual Boundsⓘ | 71.36734650 (ALPHAECP) 71.37188490 (ANTIGONE) 71.37194741 (BARON) 71.37194779 (BONMIN) 71.37190109 (COUENNE) 71.37194798 (CPLEX) 71.37185210 (GUROBI) 71.37194798 (LINDO) 71.37194399 (SCIP) 71.37194798 (SHOT) |
| Referencesⓘ | Kronqvist, Jan and Misener, Ruth, A disjunctive cut strengthening technique for convex MINLP, Tech. Rep., 2020. |
| Sourceⓘ | p_ball_10b_5p_4d.gms, contributed by Jan Kronqvist and Ruth Misener |
| Applicationⓘ | Geometry |
| Added to libraryⓘ | 26 Aug 2020 |
| Problem typeⓘ | MBQCP |
| #Variablesⓘ | 110 |
| #Binary Variablesⓘ | 50 |
| #Integer Variablesⓘ | 0 |
| #Nonlinear Variablesⓘ | 20 |
| #Nonlinear Binary Variablesⓘ | 0 |
| #Nonlinear Integer Variablesⓘ | 0 |
| Objective Senseⓘ | min |
| Objective typeⓘ | linear |
| Objective curvatureⓘ | linear |
| #Nonzeros in Objectiveⓘ | 40 |
| #Nonlinear Nonzeros in Objectiveⓘ | 0 |
| #Constraintsⓘ | 149 |
| #Linear Constraintsⓘ | 99 |
| #Quadratic Constraintsⓘ | 50 |
| #Polynomial Constraintsⓘ | 0 |
| #Signomial Constraintsⓘ | 0 |
| #General Nonlinear Constraintsⓘ | 0 |
| Operands in Gen. Nonlin. Functionsⓘ | |
| Constraints curvatureⓘ | convex |
| #Nonzeros in Jacobianⓘ | 598 |
| #Nonlinear Nonzeros in Jacobianⓘ | 200 |
| #Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 20 |
| #Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 20 |
| #Blocks in Hessian of Lagrangianⓘ | 20 |
| 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ⓘ | 1.2173e-01 |
| Maximal coefficientⓘ | 2.3881e+02 |
| Infeasibility of initial pointⓘ | 63.36 |
| Sparsity Jacobianⓘ |  |
| Sparsity Hessian of Lagrangianⓘ |  |
$offlisting
*
* Equation counts
* Total E G L N X C B
* 150 6 0 144 0 0 0 0
*
* Variable counts
* x b i s1s s2s sc si
* Total cont binary integer sos1 sos2 scont sint
* 111 61 50 0 0 0 0 0
* FX 0
*
* Nonzero counts
* Total const NL DLL
* 639 439 200 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,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,x107,x108,x109,x110,objvar;
Positive Variables 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,x107,x108,x109,x110;
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;
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,e106,e107,e108,e109,e110,e111,e112,e113,e114,e115,e116
,e117,e118,e119,e120,e121,e122,e123,e124,e125,e126,e127,e128,e129
,e130,e131,e132,e133,e134,e135,e136,e137,e138,e139,e140,e141,e142
,e143,e144,e145,e146,e147,e148,e149,e150;
e1.. x51 - x52 - x53 =L= 0;
e2.. - x51 + x52 - x53 =L= 0;
e3.. x54 - x55 - x56 =L= 0;
e4.. - x54 + x55 - x56 =L= 0;
e5.. x57 - x58 - x59 =L= 0;
e6.. - x57 + x58 - x59 =L= 0;
e7.. x60 - x61 - x62 =L= 0;
e8.. - x60 + x61 - x62 =L= 0;
e9.. x51 - x63 - x64 =L= 0;
e10.. - x51 + x63 - x64 =L= 0;
e11.. x54 - x65 - x66 =L= 0;
e12.. - x54 + x65 - x66 =L= 0;
e13.. x57 - x67 - x68 =L= 0;
e14.. - x57 + x67 - x68 =L= 0;
e15.. x60 - x69 - x70 =L= 0;
e16.. - x60 + x69 - x70 =L= 0;
e17.. x51 - x71 - x72 =L= 0;
e18.. - x51 + x71 - x72 =L= 0;
e19.. x54 - x73 - x74 =L= 0;
e20.. - x54 + x73 - x74 =L= 0;
e21.. x57 - x75 - x76 =L= 0;
e22.. - x57 + x75 - x76 =L= 0;
e23.. x60 - x77 - x78 =L= 0;
e24.. - x60 + x77 - x78 =L= 0;
e25.. x51 - x79 - x80 =L= 0;
e26.. - x51 + x79 - x80 =L= 0;
e27.. x54 - x81 - x82 =L= 0;
e28.. - x54 + x81 - x82 =L= 0;
e29.. x57 - x83 - x84 =L= 0;
e30.. - x57 + x83 - x84 =L= 0;
e31.. x60 - x85 - x86 =L= 0;
e32.. - x60 + x85 - x86 =L= 0;
e33.. x52 - x63 - x87 =L= 0;
e34.. - x52 + x63 - x87 =L= 0;
e35.. x55 - x65 - x88 =L= 0;
e36.. - x55 + x65 - x88 =L= 0;
e37.. x58 - x67 - x89 =L= 0;
e38.. - x58 + x67 - x89 =L= 0;
e39.. x61 - x69 - x90 =L= 0;
e40.. - x61 + x69 - x90 =L= 0;
e41.. x52 - x71 - x91 =L= 0;
e42.. - x52 + x71 - x91 =L= 0;
e43.. x55 - x73 - x92 =L= 0;
e44.. - x55 + x73 - x92 =L= 0;
e45.. x58 - x75 - x93 =L= 0;
e46.. - x58 + x75 - x93 =L= 0;
e47.. x61 - x77 - x94 =L= 0;
e48.. - x61 + x77 - x94 =L= 0;
e49.. x52 - x79 - x95 =L= 0;
e50.. - x52 + x79 - x95 =L= 0;
e51.. x55 - x81 - x96 =L= 0;
e52.. - x55 + x81 - x96 =L= 0;
e53.. x58 - x83 - x97 =L= 0;
e54.. - x58 + x83 - x97 =L= 0;
e55.. x61 - x85 - x98 =L= 0;
e56.. - x61 + x85 - x98 =L= 0;
e57.. x63 - x71 - x99 =L= 0;
e58.. - x63 + x71 - x99 =L= 0;
e59.. x65 - x73 - x100 =L= 0;
e60.. - x65 + x73 - x100 =L= 0;
e61.. x67 - x75 - x101 =L= 0;
e62.. - x67 + x75 - x101 =L= 0;
e63.. x69 - x77 - x102 =L= 0;
e64.. - x69 + x77 - x102 =L= 0;
e65.. x63 - x79 - x103 =L= 0;
e66.. - x63 + x79 - x103 =L= 0;
e67.. x65 - x81 - x104 =L= 0;
e68.. - x65 + x81 - x104 =L= 0;
e69.. x67 - x83 - x105 =L= 0;
e70.. - x67 + x83 - x105 =L= 0;
e71.. x69 - x85 - x106 =L= 0;
e72.. - x69 + x85 - x106 =L= 0;
e73.. x71 - x79 - x107 =L= 0;
e74.. - x71 + x79 - x107 =L= 0;
e75.. x73 - x81 - x108 =L= 0;
e76.. - x73 + x81 - x108 =L= 0;
e77.. x75 - x83 - x109 =L= 0;
e78.. - x75 + x83 - x109 =L= 0;
e79.. x77 - x85 - x110 =L= 0;
e80.. - x77 + x85 - x110 =L= 0;
e81.. sqr(0.305036966445776 - x51) + sqr(0.634555091335016 - x54) + sqr(
6.814471824267 - x57) + sqr(9.81321087468808 - x60) + 238.813652394403*b1
=L= 239.813652394403;
e82.. sqr(9.87450535964623 - x51) + sqr(8.74510685597449 - x54) + sqr(
6.66545658580281 - x57) + sqr(2.5700184949339 - x60)
+ 238.813652394403*b2 =L= 239.813652394403;
e83.. sqr(2.82885264202444 - x51) + sqr(8.4688333544494 - x54) + sqr(
5.84225640580202 - x57) + sqr(1.07461001324769 - x60)
+ 169.141574969208*b3 =L= 170.141574969208;
e84.. sqr(0.650176203261921 - x51) + sqr(3.12451267411524 - x54) + sqr(
7.75486658597646 - x57) + sqr(3.46468314918323 - x60)
+ 152.543792630283*b4 =L= 153.543792630283;
e85.. sqr(2.16828333327622 - x51) + sqr(4.30483407264652 - x54) + sqr(
6.42640527388037 - x57) + sqr(4.13540922307827 - x60)
+ 111.116543819038*b5 =L= 112.116543819038;
e86.. sqr(6.57828234352298 - x51) + sqr(9.35099743244299 - x54) + sqr(
8.54696402332509 - x57) + sqr(5.04321305427267 - x60)
+ 164.840172521363*b6 =L= 165.840172521363;
e87.. sqr(0.121730249080358 - x51) + sqr(5.5819132952254 - x54) + sqr(
1.11962957591948 - x57) + sqr(8.91043826758874 - x60)
+ 202.618528872578*b7 =L= 203.618528872578;
e88.. sqr(8.98297692267813 - x51) + sqr(1.57278944121016 - x54) + sqr(
0.373424527008207 - x57) + sqr(5.31728541389757 - x60)
+ 161.372451489157*b8 =L= 162.372451489157;
e89.. sqr(3.80876590973847 - x51) + sqr(4.52554072865087 - x54) + sqr(
2.95832977799596 - x57) + sqr(2.45196796627015 - x60)
+ 116.117810910536*b9 =L= 117.117810910536;
e90.. sqr(1.8357554909519 - x51) + sqr(7.66347281114004 - x54) + sqr(
6.23276665994841 - x57) + sqr(9.07661262817776 - x60)
+ 160.022562645954*b10 =L= 161.022562645954;
e91.. b1 + b2 + b3 + b4 + b5 + b6 + b7 + b8 + b9 + b10 =E= 1;
e92.. sqr(0.305036966445776 - x52) + sqr(0.634555091335016 - x55) + sqr(
6.814471824267 - x58) + sqr(9.81321087468808 - x61)
+ 238.813652394403*b11 =L= 239.813652394403;
e93.. sqr(9.87450535964623 - x52) + sqr(8.74510685597449 - x55) + sqr(
6.66545658580281 - x58) + sqr(2.5700184949339 - x61)
+ 238.813652394403*b12 =L= 239.813652394403;
e94.. sqr(2.82885264202444 - x52) + sqr(8.4688333544494 - x55) + sqr(
5.84225640580202 - x58) + sqr(1.07461001324769 - x61)
+ 169.141574969208*b13 =L= 170.141574969208;
e95.. sqr(0.650176203261921 - x52) + sqr(3.12451267411524 - x55) + sqr(
7.75486658597646 - x58) + sqr(3.46468314918323 - x61)
+ 152.543792630283*b14 =L= 153.543792630283;
e96.. sqr(2.16828333327622 - x52) + sqr(4.30483407264652 - x55) + sqr(
6.42640527388037 - x58) + sqr(4.13540922307827 - x61)
+ 111.116543819038*b15 =L= 112.116543819038;
e97.. sqr(6.57828234352298 - x52) + sqr(9.35099743244299 - x55) + sqr(
8.54696402332509 - x58) + sqr(5.04321305427267 - x61)
+ 164.840172521363*b16 =L= 165.840172521363;
e98.. sqr(0.121730249080358 - x52) + sqr(5.5819132952254 - x55) + sqr(
1.11962957591948 - x58) + sqr(8.91043826758874 - x61)
+ 202.618528872578*b17 =L= 203.618528872578;
e99.. sqr(8.98297692267813 - x52) + sqr(1.57278944121016 - x55) + sqr(
0.373424527008207 - x58) + sqr(5.31728541389757 - x61)
+ 161.372451489157*b18 =L= 162.372451489157;
e100.. sqr(3.80876590973847 - x52) + sqr(4.52554072865087 - x55) + sqr(
2.95832977799596 - x58) + sqr(2.45196796627015 - x61)
+ 116.117810910536*b19 =L= 117.117810910536;
e101.. sqr(1.8357554909519 - x52) + sqr(7.66347281114004 - x55) + sqr(
6.23276665994841 - x58) + sqr(9.07661262817776 - x61)
+ 160.022562645954*b20 =L= 161.022562645954;
e102.. b11 + b12 + b13 + b14 + b15 + b16 + b17 + b18 + b19 + b20 =E= 1;
e103.. sqr(0.305036966445776 - x63) + sqr(0.634555091335016 - x65) + sqr(
6.814471824267 - x67) + sqr(9.81321087468808 - x69)
+ 238.813652394403*b21 =L= 239.813652394403;
e104.. sqr(9.87450535964623 - x63) + sqr(8.74510685597449 - x65) + sqr(
6.66545658580281 - x67) + sqr(2.5700184949339 - x69)
+ 238.813652394403*b22 =L= 239.813652394403;
e105.. sqr(2.82885264202444 - x63) + sqr(8.4688333544494 - x65) + sqr(
5.84225640580202 - x67) + sqr(1.07461001324769 - x69)
+ 169.141574969208*b23 =L= 170.141574969208;
e106.. sqr(0.650176203261921 - x63) + sqr(3.12451267411524 - x65) + sqr(
7.75486658597646 - x67) + sqr(3.46468314918323 - x69)
+ 152.543792630283*b24 =L= 153.543792630283;
e107.. sqr(2.16828333327622 - x63) + sqr(4.30483407264652 - x65) + sqr(
6.42640527388037 - x67) + sqr(4.13540922307827 - x69)
+ 111.116543819038*b25 =L= 112.116543819038;
e108.. sqr(6.57828234352298 - x63) + sqr(9.35099743244299 - x65) + sqr(
8.54696402332509 - x67) + sqr(5.04321305427267 - x69)
+ 164.840172521363*b26 =L= 165.840172521363;
e109.. sqr(0.121730249080358 - x63) + sqr(5.5819132952254 - x65) + sqr(
1.11962957591948 - x67) + sqr(8.91043826758874 - x69)
+ 202.618528872578*b27 =L= 203.618528872578;
e110.. sqr(8.98297692267813 - x63) + sqr(1.57278944121016 - x65) + sqr(
0.373424527008207 - x67) + sqr(5.31728541389757 - x69)
+ 161.372451489157*b28 =L= 162.372451489157;
e111.. sqr(3.80876590973847 - x63) + sqr(4.52554072865087 - x65) + sqr(
2.95832977799596 - x67) + sqr(2.45196796627015 - x69)
+ 116.117810910536*b29 =L= 117.117810910536;
e112.. sqr(1.8357554909519 - x63) + sqr(7.66347281114004 - x65) + sqr(
6.23276665994841 - x67) + sqr(9.07661262817776 - x69)
+ 160.022562645954*b30 =L= 161.022562645954;
e113.. b21 + b22 + b23 + b24 + b25 + b26 + b27 + b28 + b29 + b30 =E= 1;
e114.. sqr(0.305036966445776 - x71) + sqr(0.634555091335016 - x73) + sqr(
6.814471824267 - x75) + sqr(9.81321087468808 - x77)
+ 238.813652394403*b31 =L= 239.813652394403;
e115.. sqr(9.87450535964623 - x71) + sqr(8.74510685597449 - x73) + sqr(
6.66545658580281 - x75) + sqr(2.5700184949339 - x77)
+ 238.813652394403*b32 =L= 239.813652394403;
e116.. sqr(2.82885264202444 - x71) + sqr(8.4688333544494 - x73) + sqr(
5.84225640580202 - x75) + sqr(1.07461001324769 - x77)
+ 169.141574969208*b33 =L= 170.141574969208;
e117.. sqr(0.650176203261921 - x71) + sqr(3.12451267411524 - x73) + sqr(
7.75486658597646 - x75) + sqr(3.46468314918323 - x77)
+ 152.543792630283*b34 =L= 153.543792630283;
e118.. sqr(2.16828333327622 - x71) + sqr(4.30483407264652 - x73) + sqr(
6.42640527388037 - x75) + sqr(4.13540922307827 - x77)
+ 111.116543819038*b35 =L= 112.116543819038;
e119.. sqr(6.57828234352298 - x71) + sqr(9.35099743244299 - x73) + sqr(
8.54696402332509 - x75) + sqr(5.04321305427267 - x77)
+ 164.840172521363*b36 =L= 165.840172521363;
e120.. sqr(0.121730249080358 - x71) + sqr(5.5819132952254 - x73) + sqr(
1.11962957591948 - x75) + sqr(8.91043826758874 - x77)
+ 202.618528872578*b37 =L= 203.618528872578;
e121.. sqr(8.98297692267813 - x71) + sqr(1.57278944121016 - x73) + sqr(
0.373424527008207 - x75) + sqr(5.31728541389757 - x77)
+ 161.372451489157*b38 =L= 162.372451489157;
e122.. sqr(3.80876590973847 - x71) + sqr(4.52554072865087 - x73) + sqr(
2.95832977799596 - x75) + sqr(2.45196796627015 - x77)
+ 116.117810910536*b39 =L= 117.117810910536;
e123.. sqr(1.8357554909519 - x71) + sqr(7.66347281114004 - x73) + sqr(
6.23276665994841 - x75) + sqr(9.07661262817776 - x77)
+ 160.022562645954*b40 =L= 161.022562645954;
e124.. b31 + b32 + b33 + b34 + b35 + b36 + b37 + b38 + b39 + b40 =E= 1;
e125.. sqr(0.305036966445776 - x79) + sqr(0.634555091335016 - x81) + sqr(
6.814471824267 - x83) + sqr(9.81321087468808 - x85)
+ 238.813652394403*b41 =L= 239.813652394403;
e126.. sqr(9.87450535964623 - x79) + sqr(8.74510685597449 - x81) + sqr(
6.66545658580281 - x83) + sqr(2.5700184949339 - x85)
+ 238.813652394403*b42 =L= 239.813652394403;
e127.. sqr(2.82885264202444 - x79) + sqr(8.4688333544494 - x81) + sqr(
5.84225640580202 - x83) + sqr(1.07461001324769 - x85)
+ 169.141574969208*b43 =L= 170.141574969208;
e128.. sqr(0.650176203261921 - x79) + sqr(3.12451267411524 - x81) + sqr(
7.75486658597646 - x83) + sqr(3.46468314918323 - x85)
+ 152.543792630283*b44 =L= 153.543792630283;
e129.. sqr(2.16828333327622 - x79) + sqr(4.30483407264652 - x81) + sqr(
6.42640527388037 - x83) + sqr(4.13540922307827 - x85)
+ 111.116543819038*b45 =L= 112.116543819038;
e130.. sqr(6.57828234352298 - x79) + sqr(9.35099743244299 - x81) + sqr(
8.54696402332509 - x83) + sqr(5.04321305427267 - x85)
+ 164.840172521363*b46 =L= 165.840172521363;
e131.. sqr(0.121730249080358 - x79) + sqr(5.5819132952254 - x81) + sqr(
1.11962957591948 - x83) + sqr(8.91043826758874 - x85)
+ 202.618528872578*b47 =L= 203.618528872578;
e132.. sqr(8.98297692267813 - x79) + sqr(1.57278944121016 - x81) + sqr(
0.373424527008207 - x83) + sqr(5.31728541389757 - x85)
+ 161.372451489157*b48 =L= 162.372451489157;
e133.. sqr(3.80876590973847 - x79) + sqr(4.52554072865087 - x81) + sqr(
2.95832977799596 - x83) + sqr(2.45196796627015 - x85)
+ 116.117810910536*b49 =L= 117.117810910536;
e134.. sqr(1.8357554909519 - x79) + sqr(7.66347281114004 - x81) + sqr(
6.23276665994841 - x83) + sqr(9.07661262817776 - x85)
+ 160.022562645954*b50 =L= 161.022562645954;
e135.. b41 + b42 + b43 + b44 + b45 + b46 + b47 + b48 + b49 + b50 =E= 1;
e136.. b1 + b11 + b21 + b31 + b41 =L= 1;
e137.. b2 + b12 + b22 + b32 + b42 =L= 1;
e138.. b3 + b13 + b23 + b33 + b43 =L= 1;
e139.. b4 + b14 + b24 + b34 + b44 =L= 1;
e140.. b5 + b15 + b25 + b35 + b45 =L= 1;
e141.. b6 + b16 + b26 + b36 + b46 =L= 1;
e142.. b7 + b17 + b27 + b37 + b47 =L= 1;
e143.. b8 + b18 + b28 + b38 + b48 =L= 1;
e144.. b9 + b19 + b29 + b39 + b49 =L= 1;
e145.. b10 + b20 + b30 + b40 + b50 =L= 1;
e146.. x51 - x52 =L= 0;
e147.. x52 - x63 =L= 0;
e148.. x63 - x71 =L= 0;
e149.. x71 - x79 =L= 0;
e150.. - x53 - x56 - x59 - x62 - x64 - x66 - x68 - x70 - x72 - x74 - x76 - x78
- x80 - x82 - x84 - x86 - x87 - x88 - x89 - x90 - x91 - x92 - x93 - x94
- x95 - x96 - x97 - x98 - x99 - x100 - x101 - x102 - x103 - x104 - x105
- x106 - x107 - x108 - x109 - x110 + objvar =E= 0;
* set non-default bounds
x51.up = 10;
x52.up = 10;
x53.up = 10;
x54.up = 10;
x55.up = 10;
x56.up = 10;
x57.up = 10;
x58.up = 10;
x59.up = 10;
x60.up = 10;
x61.up = 10;
x62.up = 10;
x63.up = 10;
x64.up = 10;
x65.up = 10;
x66.up = 10;
x67.up = 10;
x68.up = 10;
x69.up = 10;
x70.up = 10;
x71.up = 10;
x72.up = 10;
x73.up = 10;
x74.up = 10;
x75.up = 10;
x76.up = 10;
x77.up = 10;
x78.up = 10;
x79.up = 10;
x80.up = 10;
x81.up = 10;
x82.up = 10;
x83.up = 10;
x84.up = 10;
x85.up = 10;
x86.up = 10;
x87.up = 10;
x88.up = 10;
x89.up = 10;
x90.up = 10;
x91.up = 10;
x92.up = 10;
x93.up = 10;
x94.up = 10;
x95.up = 10;
x96.up = 10;
x97.up = 10;
x98.up = 10;
x99.up = 10;
x100.up = 10;
x101.up = 10;
x102.up = 10;
x103.up = 10;
x104.up = 10;
x105.up = 10;
x106.up = 10;
x107.up = 10;
x108.up = 10;
x109.up = 10;
x110.up = 10;
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