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A Library of Mixed-Integer and Continuous Nonlinear Programming Instances

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Instance wastewater11m1

Formats ams gms lp mod nl osil pip py
Primal Bounds (infeas ≤ 1e-08)
2149.02381000 p1 ( gdx sol )
(infeas: 7e-12)
2127.11538500 p2 ( gdx sol )
(infeas: 3e-11)
Other points (infeas > 1e-08)  
Dual Bounds
2127.11538200 (ANTIGONE)
2127.11538200 (BARON)
1579.13954400 (COUENNE)
2127.11538500 (GUROBI)
1697.21732400 (LINDO)
2126.91776800 (SCIP)
References Castro, Pedro M, Matos, Henrique A, and Novais, Augusto Q, An efficient heuristic procedure for the optimal design of wastewater treatment systems, Resources, Conservation and Recycling, 50:2, 2007, 158-185.
Castro, Pedro M, Teles, João P, and Novais, Augusto Q, Linear program-based algorithm for the optimal design of wastewater treatment systems, Clean Technologies and Environmental Policy, 11:1, 2009, 83-93.
Source ANTIGONE test library model Other_MIQCQP/castro_etal_2007_wts_Ex11_M1.gms
Application Waste Water Treatment
Added to library 15 Aug 2014
Problem type QCP
#Variables 118
#Binary Variables 0
#Integer Variables 0
#Nonlinear Variables 77
#Nonlinear Binary Variables 0
#Nonlinear Integer Variables 0
Objective Sense min
Objective type linear
Objective curvature linear
#Nonzeros in Objective 7
#Nonlinear Nonzeros in Objective 0
#Constraints 42
#Linear Constraints 34
#Quadratic Constraints 8
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions  
Constraints curvature indefinite
#Nonzeros in Jacobian 395
#Nonlinear Nonzeros in Jacobian 126
#Nonzeros in (Upper-Left) Hessian of Lagrangian 126
#Nonzeros in Diagonal of Hessian of Lagrangian 0
#Blocks in Hessian of Lagrangian 14
Minimal blocksize in Hessian of Lagrangian 2
Maximal blocksize in Hessian of Lagrangian 9
Average blocksize in Hessian of Lagrangian 5.5
#Semicontinuities 0
#Nonlinear Semicontinuities 0
#SOS type 1 0
#SOS type 2 0
Minimal coefficient 1.0000e-01
Maximal coefficient 5.0000e+02
Infeasibility of initial point 450
Sparsity Jacobian Sparsity of Objective Gradient and Jacobian
Sparsity Hessian of Lagrangian Sparsity of Hessian of Lagrangian

$offlisting
*  
*  Equation counts
*      Total        E        G        L        N        X        C        B
*         43       35        0        8        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*        119      119        0        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*        403      277      126        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,x107,x108,x109,x110,x111,x112,x113,x114,x115,x116
          ,x117,x118,objvar;

Positive 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,x107,x108,x109,x110,x111,x112,x113,x114
          ,x115,x116,x117,x118;

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;


e1..  - x112 - x113 - x114 - x115 - x116 - x117 - x118 + objvar =E= 0;

e2..  - x64 - x76 - x77 - x78 - x79 - x80 - x81 - x82 =E= -80;

e3..  - x65 - x83 - x84 - x85 - x86 - x87 - x88 - x89 =E= -450;

e4..  - x66 - x90 - x91 - x92 - x93 - x94 - x95 - x96 =E= -230;

e5..  - x67 - x97 - x98 - x99 - x100 - x101 - x102 - x103 =E= -90;

e6..  - x68 - x104 - x105 - x106 - x107 - x108 - x109 - x110 =E= -330;

e7..  - x15 - x22 - x29 - x36 - x43 - x50 - x57 - x76 - x83 - x90 - x97 - x104
      + x112 =E= 0;

e8..  - x16 - x23 - x30 - x37 - x44 - x51 - x58 - x77 - x84 - x91 - x98 - x105
      + x113 =E= 0;

e9..  - x17 - x24 - x31 - x38 - x45 - x52 - x59 - x78 - x85 - x92 - x99 - x106
      + x114 =E= 0;

e10..  - x18 - x25 - x32 - x39 - x46 - x53 - x60 - x79 - x86 - x93 - x100
       - x107 + x115 =E= 0;

e11..  - x19 - x26 - x33 - x40 - x47 - x54 - x61 - x80 - x87 - x94 - x101
       - x108 + x116 =E= 0;

e12..  - x20 - x27 - x34 - x41 - x48 - x55 - x62 - x81 - x88 - x95 - x102
       - x109 + x117 =E= 0;

e13..  - x21 - x28 - x35 - x42 - x49 - x56 - x63 - x82 - x89 - x96 - x103
       - x110 + x118 =E= 0;

e14..  - x15 - x16 - x17 - x18 - x19 - x20 - x21 - x69 + x112 =E= 0;

e15..  - x22 - x23 - x24 - x25 - x26 - x27 - x28 - x70 + x113 =E= 0;

e16..  - x29 - x30 - x31 - x32 - x33 - x34 - x35 - x71 + x114 =E= 0;

e17..  - x36 - x37 - x38 - x39 - x40 - x41 - x42 - x72 + x115 =E= 0;

e18..  - x43 - x44 - x45 - x46 - x47 - x48 - x49 - x73 + x116 =E= 0;

e19..  - x50 - x51 - x52 - x53 - x54 - x55 - x56 - x74 + x117 =E= 0;

e20..  - x57 - x58 - x59 - x60 - x61 - x62 - x63 - x75 + x118 =E= 0;

e21..  - x64 - x65 - x66 - x67 - x68 - x69 - x70 - x71 - x72 - x73 - x74 - x75
       + x111 =E= 0;

e22.. x15*x8 + x22*x9 + x29*x10 + x36*x11 + x43*x12 + x50*x13 + x57*x14 - x112*
      x1 + 12*x76 + 50*x83 + 500*x90 + 400*x97 + 120*x104 =E= 0;

e23.. x16*x8 + x23*x9 + x30*x10 + x37*x11 + x44*x12 + x51*x13 + x58*x14 - x113*
      x2 + 12*x77 + 50*x84 + 500*x91 + 400*x98 + 120*x105 =E= 0;

e24.. x17*x8 + x24*x9 + x31*x10 + x38*x11 + x45*x12 + x52*x13 + x59*x14 - x114*
      x3 + 12*x78 + 50*x85 + 500*x92 + 400*x99 + 120*x106 =E= 0;

e25.. x18*x8 + x25*x9 + x32*x10 + x39*x11 + x46*x12 + x53*x13 + x60*x14 - x115*
      x4 + 12*x79 + 50*x86 + 500*x93 + 400*x100 + 120*x107 =E= 0;

e26.. x19*x8 + x26*x9 + x33*x10 + x40*x11 + x47*x12 + x54*x13 + x61*x14 - x116*
      x5 + 12*x80 + 50*x87 + 500*x94 + 400*x101 + 120*x108 =E= 0;

e27.. x20*x8 + x27*x9 + x34*x10 + x41*x11 + x48*x12 + x55*x13 + x62*x14 - x117*
      x6 + 12*x81 + 50*x88 + 500*x95 + 400*x102 + 120*x109 =E= 0;

e28.. x21*x8 + x28*x9 + x35*x10 + x42*x11 + x49*x12 + x56*x13 + x63*x14 - x118*
      x7 + 12*x82 + 50*x89 + 500*x96 + 400*x103 + 120*x110 =E= 0;

e29..    x1 =L= 400;

e30..    x2 =L= 100;

e31..    x3 =L= 50;

e32..    x4 =L= 570;

e33..    x5 =L= 100;

e34..    x6 =L= 30;

e35..    x7 =L= 640;

e36..  - 0.9*x1 + x8 =E= 0;

e37..  - 0.6*x2 + x9 =E= 0;

e38..  - 0.15*x3 + x10 =E= 0;

e39..  - 0.26*x4 + x11 =E= 0;

e40..  - 0.1*x5 + x12 =E= 0;

e41..  - 0.4*x6 + x13 =E= 0;

e42..  - 0.3*x7 + x14 =E= 0;

e43.. x69*x8 + x70*x9 + x71*x10 + x72*x11 + x73*x12 + x74*x13 + x75*x14
       + 12*x64 + 50*x65 + 500*x66 + 400*x67 + 120*x68 - 4*x111 =L= 0;

* set non-default bounds
x1.up = 1000000;
x2.up = 1000000;
x3.up = 1000000;
x4.up = 1000000;
x5.up = 1000000;
x6.up = 1000000;
x7.up = 1000000;
x8.up = 1000000;
x9.up = 1000000;
x10.up = 1000000;
x11.up = 1000000;
x12.up = 1000000;
x13.up = 1000000;
x14.up = 1000000;
x15.up = 1000000;
x16.up = 1000000;
x17.up = 1000000;
x18.up = 1000000;
x19.up = 1000000;
x20.up = 1000000;
x21.up = 1000000;
x22.up = 1000000;
x23.up = 1000000;
x24.up = 1000000;
x25.up = 1000000;
x26.up = 1000000;
x27.up = 1000000;
x28.up = 1000000;
x29.up = 1000000;
x30.up = 1000000;
x31.up = 1000000;
x32.up = 1000000;
x33.up = 1000000;
x34.up = 1000000;
x35.up = 1000000;
x36.up = 1000000;
x37.up = 1000000;
x38.up = 1000000;
x39.up = 1000000;
x40.up = 1000000;
x41.up = 1000000;
x42.up = 1000000;
x43.up = 1000000;
x44.up = 1000000;
x45.up = 1000000;
x46.up = 1000000;
x47.up = 1000000;
x48.up = 1000000;
x49.up = 1000000;
x50.up = 1000000;
x51.up = 1000000;
x52.up = 1000000;
x53.up = 1000000;
x54.up = 1000000;
x55.up = 1000000;
x56.up = 1000000;
x57.up = 1000000;
x58.up = 1000000;
x59.up = 1000000;
x60.up = 1000000;
x61.up = 1000000;
x62.up = 1000000;
x63.up = 1000000;
x64.up = 1000000;
x65.up = 1000000;
x66.up = 1000000;
x67.up = 1000000;
x68.up = 1000000;
x69.up = 1000000;
x70.up = 1000000;
x71.up = 1000000;
x72.up = 1000000;
x73.up = 1000000;
x74.up = 1000000;
x75.up = 1000000;
x76.up = 1000000;
x77.up = 1000000;
x78.up = 1000000;
x79.up = 1000000;
x80.up = 1000000;
x81.up = 1000000;
x82.up = 1000000;
x83.up = 1000000;
x84.up = 1000000;
x85.up = 1000000;
x86.up = 1000000;
x87.up = 1000000;
x88.up = 1000000;
x89.up = 1000000;
x90.up = 1000000;
x91.up = 1000000;
x92.up = 1000000;
x93.up = 1000000;
x94.up = 1000000;
x95.up = 1000000;
x96.up = 1000000;
x97.up = 1000000;
x98.up = 1000000;
x99.up = 1000000;
x100.up = 1000000;
x101.up = 1000000;
x102.up = 1000000;
x103.up = 1000000;
x104.up = 1000000;
x105.up = 1000000;
x106.up = 1000000;
x107.up = 1000000;
x108.up = 1000000;
x109.up = 1000000;
x110.up = 1000000;
x111.up = 1000000;
x112.up = 1000000;
x113.up = 1000000;
x114.up = 1000000;
x115.up = 1000000;
x116.up = 1000000;
x117.up = 1000000;
x118.up = 1000000;

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;


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