expfit.gms
<![CDATA[
* NLP written by GAMS Convert at 10/06/06 11:32:04
*
* Equation counts
* Total E G L N X C
* 1 1 0 0 0 0 0
*
* Variable counts
* x b i s1s s2s sc si
* Total cont binary integer sos1 sos2 scont sint
* 3 3 0 0 0 0 0 0
* FX 0 0 0 0 0 0 0 0
*
* Nonzero counts
* Total const NL DLL
* 3 1 2 0
*
* Solve m using NLP minimizing objvar;
Variables x1,x2,objvar;
Equations e1;
e1.. - (sqr((-0.25) + exp(0.25*x2)*x1) + sqr((-0.5) + exp(0.5*x2)*x1) + sqr((-
0.75) + exp(0.75*x2)*x1) + sqr((-1) + exp(x2)*x1) + sqr((-1.25) + exp(1.25
*x2)*x1) + sqr((-1.5) + exp(1.5*x2)*x1) + sqr((-1.75) + exp(1.75*x2)*x1)
+ sqr((-2) + exp(2*x2)*x1) + sqr((-2.25) + exp(2.25*x2)*x1) + sqr((-2.5)
+ exp(2.5*x2)*x1)) + objvar =E= 0;
* set non default bounds
* 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;
]]></plaintext></body>