Description

Normally, EXAMINER just examines and reports on solutions without
reporting any solutions back to GAMS.  This behavior can be changed
with the returnXxxxPoint options.  The model verifies that the
returnInitPoint option returns the correct values.

Contributor: Steve Dirkse

Small Model of Type : GAMS

Category : GAMS Test library

Main file : examin03.gms

$title EXAMINER test suite - test returnInitPoint option (EXAMIN03,SEQ=443)

$onText
Normally, EXAMINER just examines and reports on solutions without
reporting any solutions back to GAMS.  This behavior can be changed
with the returnXxxxPoint options.  The model verifies that the
returnInitPoint option returns the correct values.

Contributor: Steve Dirkse
$offText

Sets
     i   canning plants   / seattle, san-diego /
     j   markets          / new-york, chicago, topeka / ;

Parameters

     a(i)  capacity of plant i in cases
       /    seattle     350
            san-diego   600  /

     b(j)  demand at market j in cases
       /    new-york    325
            chicago     300
            topeka      275  / ;

Table d(i,j)  distance in thousands of miles
                  new-york       chicago      topeka
    seattle          2.5           1.7          1.8
    san-diego        2.5           1.8          1.4  ;

Scalar f  freight in dollars per case per thousand miles  /90/ ;

Parameter c(i,j)  transport cost in thousands of dollars per case ;

          c(i,j) = f * d(i,j) / 1000 ;

Variables
     x(i,j)  shipment quantities in cases
     z       total transportation costs in thousands of dollars ;

Positive Variable x ;

Equations
     cost        define objective function
     supply(i)   observe supply limit at plant i
     demand(j)   satisfy demand at market j ;

cost ..        z  =e=  sum((i,j), c(i,j)*x(i,j)) ;

supply(i) ..   sum(j, x(i,j))  =l=  a(i) ;

demand(j) ..   sum(i, x(i,j))  =g=  b(j) ;

Model transport /all/ ;


* first set variable levels & equation marginals
x.l('san-diego','new-york') = 325;
x.l('san-diego','chicago')  = 275;
x.l('seattle'  ,'topeka')   = 275;
x.l('seattle'  ,'chicago')  = 50;
z.l = sum{(i,j), c(i,j)*x.l(i,j)};
cost.m = 1;
supply.m(i) = 0;
demand.m(j) = 0;

* now set quantities that Examiner will recompute when asked:
*  variable marginals (i.e. reduced costs)
*  equation levels are not set, GAMS computes these when generating
*  the model
* we can set x.m to look optimal but if they are not consistent with
* x.l they are bogus anyway.
x.m(i,j) = 0;
z.m = 0;

* we can easily compute the *REAL* x.m and z.m in this case
scalar zm, zmdiff;
parameter xm(i,j), xmdiff(i,j);
zm = 0;
xm(i,j) = c(i,j) - supply.m(i) - demand.m(j);

$onEcho > examiner.opt
examineGamsPoint yes
examineInitPoint yes
returnInitPoint  yes
$offEcho

option lp=examiner;
transport.optfile=1;
Solve transport using lp minimizing z ;

zmdiff = zm - z.m;
xmdiff(i,j) = xm(i,j) - x.m(i,j);
display zm, zmdiff, xm, xmdiff;
abort$[abs(zmdiff) > 1e-6] 'bad z.m';
abort$[smax{(i,j), abs(xmdiff(i,j))} > 1e-6] 'bad x.m';