secure.gms : Secure Work Files - Example 2

**Description**

This is example 2 of the Secure Work file document. Secure work files allow us to hide selected data and formulation section of a GAMS application. The following program runs the models described in Annex G of the GAMS User's Guide. Note the use of 'license=demo'. This creates a secure demo license valid for a few hours only and allows us to experiment without having a license that allows the creation of secure work files.

**Reference**

- GAMS Development Corporation, Modeling Tool Box.

**Small Model of Type :** GAMS

**Category :** GAMS Model library

**Main file :** secure.gms

```
$title Secure Work Files - Example 2 (SECURE,SEQ=343)
$onText
This is example 2 of the Secure Work file document. Secure work files
allow us to hide selected data and formulation section of a GAMS
application. The following program runs the models described in Annex
G of the GAMS User's Guide.
Note the use of 'license=demo'. This creates a secure demo license valid for
a few hours only and allows us to experiment without having a license that
allows the creation of secure work files.
GAMS Development Corporation, Modeling Tool Box.
Keywords: constrained nonlinear system, nonlinear programming, GAMS language features,
secure work files
$offText
$set env ide=%gams.ide% lo=%gams.lo%
execute 'gams p1 s=p1 %env%';
execute 'gams u1 r=p1 %env%';
execute 'gams s1 r=p1 s=s1 license=demo plicense=license %env%';
execute 'gams u1 s=s1 %env%';
$onEcho > p1.gms
$call gamslib -q trnsport
$include trnsport.gms
* calculate input data -- model getc
Variable newc(i,j) 'new transport cost';
Equation defnewc(i,j) 'definition of new transport cost';
Model getc 'compute new transport data' / defnewc /;
defnewc(i,j).. newc(i,j) =e= f*d(i,j)/1000;
solve getc using cns;
* change objective function and save base value of x -- model newtrans
Scalar beta 'scale coeffisinet' / 1.1 /;
Equation newcost 'definition of new objective function';
Model newtrans / newcost, supply, demand /;
newcost.. z =e= sum((i,j), newc.l(i,j)*x(i,j)**beta);
solve newtrans using nlp minimizing z;
Parameter basex(i,j) 'base value of x';
basex(i,j) = x.l(i,j);
* transform results to percentage change -- model rep
Variable delta(i,j) 'percentage chnage from base value';
Equation defdelta(i,j) 'define delta';
Model rep / defdelta /;
defdelta(i,j)$basex(i,j).. delta(i,j) =e= 100*(x.l(i,j) - basex(i,j))/basex(i,j);
solve rep using cns;
$offEcho
$onEcho > u1.gms
Set s / one, two, three /;
Parameter
sbeta(s) / one 1.25, two 1.5, three 2.0 /
sf(s) / one 85, two 75, three 50 /;
Parameter report 'summary report';
loop(s,
beta = sbeta(s);
f = sf(s);
solve getc using cns;
solve newtrans using nlp minmizing z;
solve rep using cns;
report(i,j,s) = delta.l(i,j);
report('','beta',s) = beta;
report('','f',s) = f;
report('obj','z',s) = z.l;
);
display report;
$offEcho
$onEcho > s1.gms
$hide all
$expose getc newtrans rep
$expose i j z delta
$expose f beta a b
$offEcho
```