ex14_2_5.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 ex14.2.5.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 13:40:29
*
* Equation counts
* Total E G L N X
* 6 2 0 4 0 0
*
* Variable counts
* x b i s1s s2s sc si
* Total cont binary integer sos1 sos2 scont sint
* 5 5 0 0 0 0 0 0
* FX 0 0 0 0 0 0 0 0
*
* Nonzero counts
* Total const NL DLL
* 20 8 12 0
*
* Solve m using NLP minimizing objvar;
Variables x1,x2,x3,objvar,x5;
Positive Variables x5;
Equations e1,e2,e3,e4,e5,e6;
e1.. objvar - x5 =E= 0;
e2.. 0.361872516756437*x2/(x1 + 0.888649896608059*x2) + 0.868134622480909*x2/(
0.696880695582072*x1 + x2) - (0.361872516756437*x1*x2/sqr(x1 +
0.888649896608059*x2) + 0.604986259573375*x2*x1/sqr(0.696880695582072*x1
+ x2)) - 2755.64173589155/(219.161 + x3) - x5 =L= -9.20816767045657;
e3.. 0.868134622480909*x1/(0.696880695582072*x1 + x2) + 0.361872516756437*x1/(
x1 + 0.888649896608059*x2) - (0.321577974600906*x1*x2/sqr(x1 +
0.888649896608059*x2) + 0.868134622480909*x2*x1/sqr(0.696880695582072*x1
+ x2)) - 4117.06819797521/(227.438 + x3) - x5 =L= -12.6599269316621;
e4.. (-0.361872516756437*x2/(x1 + 0.888649896608059*x2)) - 0.868134622480909*x2
/(0.696880695582072*x1 + x2) + 0.361872516756437*x1*x2/sqr(x1 +
0.888649896608059*x2) + 0.604986259573375*x2*x1/sqr(0.696880695582072*x1
+ x2) + 2755.64173589155/(219.161 + x3) - x5 =L= 9.20816767045657;
e5.. (-0.868134622480909*x1/(0.696880695582072*x1 + x2)) - 0.361872516756437*x1
/(x1 + 0.888649896608059*x2) + 0.321577974600906*x1*x2/sqr(x1 +
0.888649896608059*x2) + 0.868134622480909*x2*x1/sqr(0.696880695582072*x1
+ x2) + 4117.06819797521/(227.438 + x3) - x5 =L= 12.6599269316621;
e6.. x1 + x2 =E= 1;
* set non default bounds
x1.lo = 1E-6; x1.up = 1;
x2.lo = 1E-6; x2.up = 1;
x3.lo = 60; x3.up = 100;
* set non default levels
x1.l = 0.937;
x3.l = 80.166;
* 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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