examin04.gms : EXAMINER test suite - test returnGamsPoint option and QCP

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
returnGamsPoint option returns the correct values.

A wrinkle added here is that we test while solving as a QCP.
The test EXAMIN03 does a similar test, but for LP.

Contributors: Tom Rutherford & Steve Dirkse


Small Model of Type : GAMS


Category : GAMS Test library


Main file : examin04.gms

$TITLE EXAMINER test suite - test returnGamsPoint option and QCP(EXAMIN04,SEQ=464)

$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
returnGamsPoint option returns the correct values.

A wrinkle added here is that we test while solving as a QCP.
The test EXAMIN03 does a similar test, but for LP.

Contributors: Tom Rutherford & 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/ ;

transport.optfile = 1;

$onecho >examiner.opt
examineinitpoint=1
returngamspoint=1
$offecho

option qcp=examiner;

Solve transport using qcp minimizing z ;

abort$[transport.modelstat <> 6] 'bad modelstat';
abort$[transport.solvestat <> 4] 'bad solvestat';
abort$[transport.numinfes <> 3]  'bad numinfes';