Hi everyone,

I am still trying to figure out how EMP and Stochastic Programming work together.

Therefore I used the example from the Library https://www.gams.com/35/docs/UG_EMP_SP.html

I added a new set “t” so that the demand varies over time. However, I do not understand (even if I tried several options) how to solve the model with more than one entry in the set “t”.

If I solve the model with more than one entry it abords due to the error " Distribution function for variable 10 is not parametric". From my perspective, this is an error connected to the emp.info. In specific this line:

```
randvar d normal 45 10
```

As long as the value (“45”) matches the value of the parameter d(t) (“45”) everything is fine. Of course in another time period (e.g. t2) i want to have a different demand than 45. But than the error mentioned above pops up. Long story short… How can i implement different values in the EMP (without using LINDO).

I do not know how to solve it

Hopefully, someone can help!

This is the full code:

```
Set t /t1*t2/
Variable z "profit";
Positive Variables
x(t) "units bought"
i(t) "inventory"
l(t) "lost sales"
s(t) "units sold";
Scalars c "purchase costs per unit" / 30 /
p "penalty shortage cost per unit" / 5 /
h "holding cost per leftover unit" / 10 /
v "revenue per unit sold" / 60 /
parameter d(t) Demand
/
t1 45
t2 49
*t3 48
*t4 35
*
/;
Equations profit "profit to be maximized"
row1 "demand = UnitsSold + LostSales"
row2 "inventory = UnitsBought - UnitsSold";
profit.. z =e= sum(t, v*s(t) - c*x(t) - h*i(t) - p*l(t));
row1(t).. d(t) =e= s(t) + l(t);
row2(t).. i(t) =e= x(t) - s(t);
File emp / '%emp.info%' /;
put emp '* problem %gams.i%'/;
$onput
randvar d normal 45 10
sample d 3
stage 2 i l s d
stage 2 Row1 Row2
$offput
putclose emp;
Set scen "scenarios" / s1*s3 /;
Parameter
s_d(scen,t) "demand realization by scenario"
s_x(scen,t) "units bought by scenario"
s_s(scen,t) "units sold by scenario"
s_rep(scen,*) "scenario probability" / #scen.prob 0 /;
Set dict / scen .scenario.''
d .randvar .s_d
s .level .s_s
x .level .s_x
'' .opt .s_rep /;
Model nv / all /;
solve nv max z use EMP scenario dict;
execute_unload "EMP"
```

I know