sep1.gms:
References:
- Floudas, C A, and Schweiger, C A, MINOPT Model Library.
- Kocis, G R, and Grossmann, I E, A Modeling and Decomposition Strategy for the MINLP Optimization of Process Flowsheets. Computers and Chemical Engineering 13, 7 (1989), 797-819.
- Original source: MINOPT model kocis87-2.dat from MINOPT Model Library
Point:
p1
Best known point (p1): Solution value -510.08 (global optimum, BARON certificate)
<![CDATA[
$offlisting
* MINLP written by GAMS Convert at 04/17/01 16:41:11
*
* Equation counts
* Total E G L N X
* 32 23 5 4 0 0
*
* Variable counts
* x b i s1s s2s sc si
* Total cont binary integer sos1 sos2 scont sint
* 30 28 2 0 0 0 0 0
* FX 0 0 0 0 0 0 0 0
*
* Nonzero counts
* Total const NL DLL
* 99 87 12 0
*
* Solve m using MINLP 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,b28,b29,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;
Binary Variables b28,b29;
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;
e1.. - 0.55*x5 - 0.5*x6 + x7 =E= 0;
e2.. - 0.45*x5 - 0.5*x6 + x8 =E= 0;
e3.. - x25*x7 + x9 =E= 0;
e4.. - x25*x8 + x10 =E= 0;
e5.. - x26*x7 + x11 =E= 0;
e6.. - x26*x8 + x12 =E= 0;
e7.. - x27*x7 + x13 =E= 0;
e8.. - x27*x8 + x14 =E= 0;
e9.. - x7 + x9 + x11 + x13 + x15 =E= 0;
e10.. - x8 + x10 + x12 + x14 + x16 =E= 0;
e11.. - 0.85*x9 + x17 =E= 0;
e12.. - 0.2*x10 + x18 =E= 0;
e13.. - 0.15*x9 + x19 =E= 0;
e14.. - 0.8*x10 + x20 =E= 0;
e15.. - 0.975*x11 + x21 =E= 0;
e16.. - 0.05*x12 + x22 =E= 0;
e17.. - 0.025*x11 + x23 =E= 0;
e18.. - 0.95*x12 + x24 =E= 0;
e19.. x1 - x13 - x17 - x21 =E= 0;
e20.. x2 - x14 - x18 - x22 =E= 0;
e21.. x3 - x15 - x19 - x23 =E= 0;
e22.. x4 - x16 - x20 - x24 =E= 0;
e23.. x9 + x10 - 2.5*b29 =G= 0;
e24.. x9 + x10 - 25*b29 =L= 0;
e25.. x11 + x12 - 2.5*b28 =G= 0;
e26.. x11 + x12 - 25*b28 =L= 0;
e27.. x1 - 4*x2 =G= 0;
e28.. - 3*x3 + x4 =G= 0;
e29.. x1 + x2 =L= 15;
e30.. x3 + x4 =L= 18;
e31.. b28 + b29 =G= 1;
e32.. 35*x1 + 30*x4 - 10*x5 - 8*x6 - x9 - x10 - 4*x11 - 4*x12 - 50*b28
- 2*b29 + objvar =E= 0;
* set non default bounds
x1.up = 50;
x2.up = 50;
x3.up = 50;
x4.up = 50;
x5.up = 25;
x6.up = 25;
x7.up = 50;
x8.up = 50;
x9.up = 50;
x10.up = 50;
x11.up = 50;
x12.up = 50;
x13.up = 50;
x14.up = 50;
x15.up = 50;
x16.up = 50;
x17.up = 50;
x18.up = 50;
x19.up = 50;
x20.up = 50;
x21.up = 50;
x22.up = 50;
x23.up = 50;
x24.up = 50;
x25.up = 1;
x26.up = 1;
x27.up = 1;
$if set nostart $goto modeldef
* set non default levels
x1.l = 10;
x2.l = 2.5;
x3.l = 4;
x4.l = 14;
x5.l = 8;
x6.l = 25;
x25.l = 0.1;
x26.l = 0.1;
x27.l = 0.1;
b28.l = 0.5;
b29.l = 0.5;
* set non default marginals
$label modeldef
Model m / all /;
m.limrow=0; m.limcol=0;
$if NOT '%gams.u1%' == '' $include '%gams.u1%'
$if not set MINLP $set MINLP MINLP
Solve m using %MINLP% minimizing objvar;
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