ex14_2_3.gms:
Reference:
- Floudas, C A, Pardalos, P M, Adjiman, C S, Esposito, W R, Gumus, Z H, Harding, S T, Klepeis, J L, Meyer, C A, and Schweiger, C A, Handbook of Test Problems in Local and Global Optimization. Kluwer Academic Publishers, 1999.
- Original source: Global Model of Chapter 14 ex14.2.3.gms from Floudas e.a. Test Problems
Point:
p1
Best known point: p1 with value 0.0000
<![CDATA[
* NLP written by GAMS Convert at 07/19/01 13:40:28
*
* Equation counts
* Total E G L N X
* 10 2 0 8 0 0
*
* Variable counts
* x b i s1s s2s sc si
* Total cont binary integer sos1 sos2 scont sint
* 7 7 0 0 0 0 0 0
* FX 0 0 0 0 0 0 0 0
*
* Nonzero counts
* Total const NL DLL
* 54 14 40 0
*
* Solve m using NLP minimizing objvar;
Variables x1,x2,x3,x4,x5,objvar,x7;
Positive Variables x7;
Equations e1,e2,e3,e4,e5,e6,e7,e8,e9,e10;
e1.. objvar - x7 =E= 0;
e2.. log(x1 + 1.2689544013438*x2 + 0.696334182309743*x3 + 0.590071729272002*x4)
+ x1/(x1 + 1.2689544013438*x2 + 0.696334182309743*x3 + 0.590071729272002*
x4) + 1.55190688128384*x2/(1.55190688128384*x1 + x2 + 0.696676834276998*x3
+ 1.27289874839144*x4) + 0.767395887387844*x3/(0.767395887387844*x1 +
0.176307940228365*x2 + x3 + 0.187999658986436*x4) + 0.989870205661735*x4/(
0.989870205661735*x1 + 0.928335072476283*x2 + 0.308103094315467*x3 + x4)
+ 2787.49800065313/(229.664 + x5) - x7 =L= 10.7545020354713;
e3.. log(1.55190688128384*x1 + x2 + 0.696676834276998*x3 + 1.27289874839144*x4)
+ 1.2689544013438*x1/(x1 + 1.2689544013438*x2 + 0.696334182309743*x3 +
0.590071729272002*x4) + x2/(1.55190688128384*x1 + x2 + 0.696676834276998*
x3 + 1.27289874839144*x4) + 0.176307940228365*x3/(0.767395887387844*x1 +
0.176307940228365*x2 + x3 + 0.187999658986436*x4) + 0.928335072476283*x4/(
0.989870205661735*x1 + 0.928335072476283*x2 + 0.308103094315467*x3 + x4)
+ 2696.24885600287/(226.232 + x5) - x7 =L= 10.3803549837107;
e4.. log(0.767395887387844*x1 + 0.176307940228365*x2 + x3 + 0.187999658986436*
x4) + 0.696334182309743*x1/(x1 + 1.2689544013438*x2 + 0.696334182309743*x3
+ 0.590071729272002*x4) + 0.696676834276998*x2/(1.55190688128384*x1 + x2
+ 0.696676834276998*x3 + 1.27289874839144*x4) + x3/(0.767395887387844*x1
+ 0.176307940228365*x2 + x3 + 0.187999658986436*x4) + 0.308103094315467*
x4/(0.989870205661735*x1 + 0.928335072476283*x2 + 0.308103094315467*x3 +
x4) + 3643.31361767678/(239.726 + x5) - x7 =L= 12.9738026256517;
e5.. log(0.989870205661735*x1 + 0.928335072476283*x2 + 0.308103094315467*x3 +
x4) + 0.590071729272002*x1/(x1 + 1.2689544013438*x2 + 0.696334182309743*x3
+ 0.590071729272002*x4) + 1.27289874839144*x2/(1.55190688128384*x1 + x2
+ 0.696676834276998*x3 + 1.27289874839144*x4) + 0.187999658986436*x3/(
0.767395887387844*x1 + 0.176307940228365*x2 + x3 + 0.187999658986436*x4)
+ x4/(0.989870205661735*x1 + 0.928335072476283*x2 + 0.308103094315467*x3
+ x4) + 2755.64173589155/(219.161 + x5) - x7 =L= 10.2081676704566;
e6.. (-log(x1 + 1.2689544013438*x2 + 0.696334182309743*x3 + 0.590071729272002*
x4)) - (x1/(x1 + 1.2689544013438*x2 + 0.696334182309743*x3 +
0.590071729272002*x4) + 1.55190688128384*x2/(1.55190688128384*x1 + x2 +
0.696676834276998*x3 + 1.27289874839144*x4) + 0.767395887387844*x3/(
0.767395887387844*x1 + 0.176307940228365*x2 + x3 + 0.187999658986436*x4)
+ 0.989870205661735*x4/(0.989870205661735*x1 + 0.928335072476283*x2 +
0.308103094315467*x3 + x4)) - 2787.49800065313/(229.664 + x5) - x7
=L= -10.7545020354713;
e7.. (-log(1.55190688128384*x1 + x2 + 0.696676834276998*x3 + 1.27289874839144*
x4)) - (1.2689544013438*x1/(x1 + 1.2689544013438*x2 + 0.696334182309743*x3
+ 0.590071729272002*x4) + x2/(1.55190688128384*x1 + x2 +
0.696676834276998*x3 + 1.27289874839144*x4) + 0.176307940228365*x3/(
0.767395887387844*x1 + 0.176307940228365*x2 + x3 + 0.187999658986436*x4)
+ 0.928335072476283*x4/(0.989870205661735*x1 + 0.928335072476283*x2 +
0.308103094315467*x3 + x4)) - 2696.24885600287/(226.232 + x5) - x7
=L= -10.3803549837107;
e8.. (-log(0.767395887387844*x1 + 0.176307940228365*x2 + x3 + 0.187999658986436
*x4)) - (0.696334182309743*x1/(x1 + 1.2689544013438*x2 + 0.696334182309743
*x3 + 0.590071729272002*x4) + 0.696676834276998*x2/(1.55190688128384*x1 +
x2 + 0.696676834276998*x3 + 1.27289874839144*x4) + x3/(0.767395887387844*
x1 + 0.176307940228365*x2 + x3 + 0.187999658986436*x4) + 0.308103094315467
*x4/(0.989870205661735*x1 + 0.928335072476283*x2 + 0.308103094315467*x3 +
x4)) - 3643.31361767678/(239.726 + x5) - x7 =L= -12.9738026256517;
e9.. (-log(0.989870205661735*x1 + 0.928335072476283*x2 + 0.308103094315467*x3
+ x4)) - (0.590071729272002*x1/(x1 + 1.2689544013438*x2 +
0.696334182309743*x3 + 0.590071729272002*x4) + 1.27289874839144*x2/(
1.55190688128384*x1 + x2 + 0.696676834276998*x3 + 1.27289874839144*x4) +
0.187999658986436*x3/(0.767395887387844*x1 + 0.176307940228365*x2 + x3 +
0.187999658986436*x4) + x4/(0.989870205661735*x1 + 0.928335072476283*x2 +
0.308103094315467*x3 + x4)) - 2755.64173589155/(219.161 + x5) - x7
=L= -10.2081676704566;
e10.. x1 + x2 + x3 + x4 =E= 1;
* set non default bounds
x1.lo = 1E-6; x1.up = 1;
x2.lo = 1E-6; x2.up = 1;
x3.lo = 1E-6; x3.up = 1;
x4.lo = 1E-6; x4.up = 1;
x5.lo = 20; x5.up = 80;
* set non default levels
x1.l = 0.295;
x2.l = 0.148;
x3.l = 0.463;
x4.l = 0.094;
x5.l = 57.154;
* set non default marginals
Model m / all /;
m.limrow=0; m.limcol=0;
$if NOT '%gams.u1%' == '' $include '%gams.u1%'
Solve m using NLP minimizing objvar;
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