MINLPLib

A Library of Mixed-Integer and Continuous Nonlinear Programming Instances

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Instance synheat

This MINLPLib instance is generated from a GAMS model library model before GAMS 51.1.0.
A bugfix to synheat from GAMS 51.1.0 has not been applied here. It would have no effect on the optimal value either.
Formats ams gms mod nl osil py
Primal Bounds (infeas ≤ 1e-08)
154997.33490000 p1 ( gdx sol )
(infeas: 6e-12)
Other points (infeas > 1e-08)  
Dual Bounds
131503.15950000 (ANTIGONE)
154997.33490000 (BARON)
145371.59180000 (COUENNE)
154993.87360000 (GUROBI)
154961.23140000 (LINDO)
154402.33420000 (SCIP)
0.00000000 (SHOT)
151108.48430000 (XPRESS)
References Yee, Terrence F and Grossmann, I E, Simultaneous Optimization of Models for Heat Integration - II. Heat Exchanger Network Synthesis, Computers and Chemical Engineering, 14:10, 1990, 1165-1184.
Source GAMS Model Library model synheat
Application Simultaneous Optimization for HEN Synthesis
Added to library 01 May 2001
Problem type MBNLP
#Variables 56
#Binary Variables 12
#Integer Variables 0
#Nonlinear Variables 28
#Nonlinear Binary Variables 0
#Nonlinear Integer Variables 0
Objective Sense min
Objective type nonlinear
Objective curvature indefinite
#Nonzeros in Objective 44
#Nonlinear Nonzeros in Objective 28
#Constraints 64
#Linear Constraints 64
#Quadratic Constraints 0
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions div mul vcpower
Constraints curvature linear
#Nonzeros in Jacobian 180
#Nonlinear Nonzeros in Jacobian 0
#Nonzeros in (Upper-Left) Hessian of Lagrangian 72
#Nonzeros in Diagonal of Hessian of Lagrangian 16
#Blocks in Hessian of Lagrangian 8
Minimal blocksize in Hessian of Lagrangian 2
Maximal blocksize in Hessian of Lagrangian 5
Average blocksize in Hessian of Lagrangian 3.5
#Semicontinuities 0
#Nonlinear Semicontinuities 0
#SOS type 1 0
#SOS type 2 0
Minimal coefficient 1.0000e-06
Maximal coefficient 2.9996e+04
Infeasibility of initial point 9200
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
*         65       21       12       32        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*         57       45       12        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*        225      197       28        0
*
*  Solve m using MINLP minimizing objvar;


Variables  b1,b2,b3,b4,b5,b6,b7,b8,b9,b10,b11,b12,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,objvar;

Positive Variables  x25,x26,x27,x28,x29,x30,x31,x32,x33,x34,x35,x36,x37,x38
          ,x39,x40;

Binary Variables  b1,b2,b3,b4,b5,b6,b7,b8,b9,b10,b11,b12;

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;


e1..    10*x13 - 10*x14 - x25 - x28 =E= 0;

e2..    10*x14 - 10*x15 - x26 - x29 =E= 0;

e3..    20*x16 - 20*x17 - x31 - x34 =E= 0;

e4..    20*x17 - 20*x18 - x32 - x35 =E= 0;

e5..    10*x15 - x37 =E= 3700;

e6..    20*x18 - x38 =E= 7400;

e7..  - x25 - x26 - x28 - x29 - x37 =E= -2800;

e8..  - x31 - x32 - x34 - x35 - x38 =E= -4400;

e9..    15*x19 - 15*x20 - x25 - x31 =E= 0;

e10..    15*x20 - 15*x21 - x26 - x32 =E= 0;

e11..    13*x22 - 13*x23 - x28 - x34 =E= 0;

e12..    13*x23 - 13*x24 - x29 - x35 =E= 0;

e13..  - 15*x19 - x39 =E= -9750;

e14..  - 13*x22 - x40 =E= -6500;

e15..  - x25 - x26 - x31 - x32 - x39 =E= -3600;

e16..  - x28 - x29 - x34 - x35 - x40 =E= -1950;

e17..    x13 - x14 =G= 0;

e18..    x14 - x15 =G= 0;

e19..    x16 - x17 =G= 0;

e20..    x17 - x18 =G= 0;

e21..    x19 - x20 =G= 0;

e22..    x20 - x21 =G= 0;

e23..    x22 - x23 =G= 0;

e24..    x23 - x24 =G= 0;

e25..    x15 =G= 370;

e26..    x18 =G= 370;

e27..  - x19 =G= -650;

e28..  - x22 =G= -500;

e29..  - x13 =E= -650;

e30..  - x16 =E= -590;

e31..  - x21 =E= -410;

e32..  - x24 =E= -350;

e33..  - 2800*b1 + x25 =L= 0;

e34..  - 2800*b2 + x26 =L= 0;

e35..  - 1950*b3 + x28 =L= 0;

e36..  - 1950*b4 + x29 =L= 0;

e37..  - 3600*b5 + x31 =L= 0;

e38..  - 3600*b6 + x32 =L= 0;

e39..  - 1950*b7 + x34 =L= 0;

e40..  - 1950*b8 + x35 =L= 0;

e41..  - 3600*b11 + x39 =L= 0;

e42..  - 1950*b12 + x40 =L= 0;

e43..  - 2800*b9 + x37 =L= 0;

e44..  - 4400*b10 + x38 =L= 0;

e45..    280*b1 - x13 + x19 + x41 =L= 280;

e46..    280*b2 - x14 + x20 + x42 =L= 280;

e47..    130*b3 - x13 + x22 + x44 =L= 130;

e48..    130*b4 - x14 + x23 + x45 =L= 130;

e49..    280*b5 - x16 + x19 + x47 =L= 280;

e50..    280*b6 - x17 + x20 + x48 =L= 280;

e51..    130*b7 - x16 + x22 + x50 =L= 130;

e52..    130*b8 - x17 + x23 + x51 =L= 130;

e53..    280*b1 - x14 + x20 + x42 =L= 280;

e54..    280*b2 - x15 + x21 + x43 =L= 280;

e55..    130*b3 - x14 + x23 + x45 =L= 130;

e56..    130*b4 - x15 + x24 + x46 =L= 130;

e57..    280*b5 - x17 + x20 + x48 =L= 280;

e58..    280*b6 - x18 + x21 + x49 =L= 280;

e59..    130*b7 - x17 + x23 + x51 =L= 130;

e60..    130*b8 - x18 + x24 + x52 =L= 130;

e61..  - x15 + x53 =L= -320;

e62..  - x18 + x54 =L= -320;

e63..    x19 + x55 =L= 680;

e64..    x22 + x56 =L= 680;

e65.. -(150*(2*x25/(1e-6 + (1e-6 + 0.5*x41*x42*(x41 + x42))**0.33333) + 2*x26/(
      1e-6 + (1e-6 + 0.5*x42*x43*(x42 + x43))**0.33333) + 2*x28/(1e-6 + (1e-6
       + 0.5*x44*x45*(x44 + x45))**0.33333) + 2*x29/(1e-6 + (1e-6 + 0.5*x45*x46
      *(x45 + x46))**0.33333) + 2*x31/(1e-6 + (1e-6 + 0.5*x47*x48*(x47 + x48))
      **0.33333) + 2*x32/(1e-6 + (1e-6 + 0.5*x48*x49*(x48 + x49))**0.33333) + 2
      *x34/(1e-6 + (1e-6 + 0.5*x50*x51*(x50 + x51))**0.33333) + 2*x35/(1e-6 + (
      1e-6 + 0.5*x51*x52*(x51 + x52))**0.33333)) + 150*(1.2*x39/(1e-6 + 30*x55*
      (15 + 0.5*x55))**0.33333 + 1.2*x40/(1e-6 + 180*x56*(90 + 0.5*x56))**
      0.33333) + 150*(2*x37/(1e-6 + 35*x53*(70 + x53))**0.33333 + 2*x38/(1e-6
       + 35*x54*(70 + x54))**0.33333) + 80*x39 + 80*x40 + 15*x37 + 15*x38)
       - 5500*b1 - 5500*b2 - 5500*b3 - 5500*b4 - 5500*b5 - 5500*b6 - 5500*b7
       - 5500*b8 - 5500*b9 - 5500*b10 - 5500*b11 - 5500*b12
       - 29995.6190569812*x27 - 29995.6190569812*x30 - 29995.6190569812*x33
       - 29995.6190569812*x36 + objvar =E= 0.0024;

* set non-default bounds
x13.lo = 370; x13.up = 650;
x14.lo = 370; x14.up = 650;
x15.lo = 370; x15.up = 650;
x16.lo = 370; x16.up = 590;
x17.lo = 370; x17.up = 590;
x18.lo = 370; x18.up = 590;
x19.lo = 410; x19.up = 650;
x20.lo = 410; x20.up = 650;
x21.lo = 410; x21.up = 650;
x22.lo = 350; x22.up = 500;
x23.lo = 350; x23.up = 500;
x24.lo = 350; x24.up = 500;
x41.lo = 10;
x42.lo = 10;
x43.lo = 10;
x44.lo = 10;
x45.lo = 10;
x46.lo = 10;
x47.lo = 10;
x48.lo = 10;
x49.lo = 10;
x50.lo = 10;
x51.lo = 10;
x52.lo = 10;
x53.lo = 10;
x54.lo = 10;
x55.lo = 10;
x56.lo = 10;

* set non-default levels
x25.l = 2800;
x26.l = 2800;
x28.l = 1950;
x29.l = 1950;
x31.l = 3600;
x32.l = 3600;
x34.l = 1950;
x35.l = 1950;
x41.l = 240;
x42.l = 240;
x43.l = 240;
x44.l = 300;
x45.l = 300;
x46.l = 300;
x47.l = 180;
x48.l = 180;
x49.l = 180;
x50.l = 240;
x51.l = 240;
x52.l = 240;
x53.l = 330;
x54.l = 270;
x55.l = 270;
x56.l = 330;

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: 2026-03-18 Git hash: de427236
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