ex14_1_2.gms:
References:
- 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.
- Meintjes, K, and Morgan, A P, Chemical-Equilibrium Systems as Numerical Test Problems. ACM Trans. Math. Soft. 16 (1990), 143-151.
- Original source: Global Model of Chapter 14 ex14.1.2.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 13:40:24
*
* 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
* 43 17 26 0
*
* Solve m using NLP minimizing objvar;
Variables x1,x2,x3,x4,x5,x6,objvar;
Equations e1,e2,e3,e4,e5,e6,e7,e8,e9,e10;
e1.. - x6 + objvar =E= 0;
e2.. x1*x2 + x1 - 3*x5 =E= 0;
e3.. 2.8845e-6*sqr(x2) + 4.4975e-7*x2 + 2*x1*x2 + x1 + 0.000545176668613029*x2*
x3 + 3.40735417883143e-5*x2*x4 + x2*sqr(x3) - 10*x5 - x6 =L= 0;
e4.. (-2.8845e-6*sqr(x2)) - 4.4975e-7*x2 - 2*x1*x2 - x1 - 0.000545176668613029*
x2*x3 - 3.40735417883143e-5*x2*x4 - x2*sqr(x3) + 10*x5 - x6 =L= 0;
e5.. 0.386*sqr(x3) + 0.000410621754172864*x3 + 0.000545176668613029*x2*x3 + 2*
x2*sqr(x3) - 8*x5 - x6 =L= 0;
e6.. (-0.386*sqr(x3)) - 0.000410621754172864*x3 - 0.000545176668613029*x2*x3 -
2*x2*sqr(x3) + 8*x5 - x6 =L= 0;
e7.. 2*sqr(x4) + 3.40735417883143e-5*x2*x4 - 40*x5 - x6 =L= 0;
e8.. (-2*sqr(x4)) - 3.40735417883143e-5*x2*x4 + 40*x5 - x6 =L= 0;
e9.. 9.615e-7*sqr(x2) + 4.4975e-7*x2 + 0.193*sqr(x3) + 0.000410621754172864*x3
+ sqr(x4) + x1*x2 + x1 + 0.000545176668613029*x2*x3 + 3.40735417883143e-5
*x2*x4 + x2*sqr(x3) - x6 =L= 1;
e10.. (-9.615e-7*sqr(x2)) - 4.4975e-7*x2 - 0.193*sqr(x3) - 0.000410621754172864
*x3 - sqr(x4) - x1*x2 - x1 - 0.000545176668613029*x2*x3 -
3.40735417883143e-5*x2*x4 - x2*sqr(x3) - x6 =L= -1;
* set non default bounds
x1.lo = 0.0001; x1.up = 100;
x2.lo = 0.0001; x2.up = 100;
x3.lo = 0.0001; x3.up = 100;
x4.lo = 0.0001; x4.up = 100;
x5.lo = 0.0001; x5.up = 100;
* set non default levels
* 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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