scenempty.gms : Empty scenario GUSS Test

Description

Previous to 24.2.3 GUSS only solved scenarios that had some update data.
Now GUSS accepts a parameter SolveEmpty that determines the maximum number of
solves without update data. In case of an "empty" solver it depends on the
update type what scenario we solve.

Contributor: Michael Bussieck, March 2014


Small Model of Type : GAMS


Category : GAMS Test library


Main file : scenempty.gms

$Title Empty scenario GUSS Test (SCENEMPTY,SEQ=648)

$Ontext
Previous to 24.2.3 GUSS only solved scenarios that had some update data.
Now GUSS accepts a parameter SolveEmpty that determines the maximum number of
solves without update data. In case of an "empty" solver it depends on the
update type what scenario we solve.

Contributor: Michael Bussieck, March 2014
$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) ;

  scalar bmod /0.1/;
  demand(j) ..   sum(i, x(i,j))  =g=  (1-bmod)*b(j) ;

  Model transport /all/ ;

  set ss / s0*s100 /, s(ss) /s4,s6*s9/;
$eval CardS card(s)
  parameter
      sbmod(ss)  / s4 0, s6 0.2, s7 0, s8 -0.01, s9 0 /
      srep(ss,*) / #s.modelstat 0, #s.solvestat 0 /
      sopt0(*)   / UpdateType 0, SolveEmpty %CardS% /
      sopt1(*)   / UpdateType 1, SolveEmpty %CardS% /
      sopt2(*)   / UpdateType 2, SolveEmpty %CardS% /
      sz(ss);

  set dict0  / s           .scenario   . ''
               sopt0       .opt        .srep
               bmod        .param      .sbmod
               z           .level      .sz    /
  set dict1  / s           .scenario   . ''
               sopt1       .opt        .srep
               bmod        .param      .sbmod
               z           .level      .sz    /
  set dict2  / s           .scenario   . ''
               sopt2       .opt        .srep
               bmod        .param      .sbmod
               z           .level      .sz    /

* UpdateType Zero + Scenario Data
  Solve transport using lp minimizing z scenario dict0;

  abort$(card(srep)<>card(s)*2) 'wrong srep', srep;
  abort$(smin(s,srep(s,'solvestat'))<>1 or
         smax(s,srep(s,'solvestat'))<>1) 'wrong solvestat', srep;
  abort$(abs(153.675-sz('s4'))>1e-6) 'wrong s4', sz;
  abort$(abs(153.675-sz('s7'))>1e-6) 'wrong s7', sz;
  abort$(abs(153.675-sz('s9'))>1e-6) 'wrong s9', sz;

* UpdateType BaseCase + Scenario data
  Solve transport using lp minimizing z scenario dict1;

  abort$(card(srep)<>card(s)*2) 'wrong srep', srep;
  abort$(smin(s,srep(s,'solvestat'))<>1 or
         smax(s,srep(s,'solvestat'))<>1) 'wrong solvestat', srep;
  abort$(abs(138.3075-sz('s4'))>1e-6) 'wrong s4', sz;
  abort$(abs(138.3075-sz('s7'))>1e-6) 'wrong s7', sz;
  abort$(abs(138.3075-sz('s9'))>1e-6) 'wrong s9', sz;

* UpdateType Previous Scenario + Scenario data
  Solve transport using lp minimizing z scenario dict2;

  abort$(card(srep)<>card(s)*2) 'wrong srep', srep;
  abort$(smin(s,srep(s,'solvestat'))<>1 or
         smax(s,srep(s,'solvestat'))<>1) 'wrong solvestat', srep;
  abort$(abs(138.3075 -sz('s4'))>1e-6) 'wrong s4', sz;
  abort$(abs(122.94   -sz('s7'))>1e-6) 'wrong s7', sz;
  abort$(abs(155.21175-sz('s9'))>1e-6) 'wrong s9', sz;