sets
t                   / 1*5 /
h                   / 1*4 /
s     sth scenario  / 1*3 /

parameters a(t) / 1 1000, 2 11, 3 1200, 4 13, 5 14 /
b(h) /
1        20
2        21
3        22
4        23/

c(s) /
1        10
2        2000
3        3  /
* this is the scenario dependent parameter

cc
* cc is c(s), used as a dummy parameter in order to solve the deterministic
* under different scenarios

variables   Z1(t),Z2(h), NPV

binary variable Y(t)

equations    e1, e2, e3 ;
e1(t)..     Z1(t) =e= (a(t) + cc)*Y(t)                 ;
e2(h)..     Z2(h) =e= -b(h)* sum(t,Y(t))             ;
e3..        NPV =e= sum[t,Z1(t)] + sum[h,Z2(h)]      ;
option solprint = off;
option limcol = 0;
option limrow = 0;
option optcr = 0.00;

model single_scenario /all/;

parameter Xc,sc,scn ;

for{sc =1 to 3,
* this 'for' statement allows performing the deterministic problem under different scenarios
     Xc(s) = 0 + 1$(ord(s)= sc);
     cc = sum[s,Xc(s)*c(s)];
* here we fix the value of cc with the correspondent values of c(s) for each scenario
     solve single_scenario using minlp minimizing NPV;
     Y.fx(t) = Y.l(t);
* we fix the solution found to obtain the NPV for each scenario under that solution found
     display Y.l;
     for[scn = 1 to 3,
         Xc(s) = 0 + 1$(ord(s)= scn);
         cc = sum[s,Xc(s)*c(s)];
         solve single_scenario using minlp minimizing NPV;
         display NPV.l, Y.l;
        ];
    Y.lo(t) = 0;
    Y.up(t) = 1;
* we let free the variables and start again.
  };