> I have some inventory variables defined by the following constraint set:
>
> inventory_1{x in X, y in Y, t in 0..20}:
> INVENT_1[x,y,t] = sum{ (i,j) in set_1 : attribute_1[i] = x and
> attribute_2[i] = y } d[t]*x[i,j];
>
> i, referenced above, can have attribute_1:= 0,1,2 in periods t = 0,1,2;
> but in all later periods, t>2, all i have attribute_1:= 0.
>
> The set X:= {0,1,2} for the entire modelling horizon; the elements {1,2}
> are redundant after t>2.
>
> Does this adversely affect model generation time?
Yes, because corresponding array members have to be found in the symbol
table whenever they are referenced.
>
> I feel like it would be faster if X:={0,1,2} when t<=2 and X:={0} when
> t>2 but I can't think of anyway to do this other than make two sets of
> constraints:
>
> e.g.,
> inventory_1a{x in Xa , y in Y, t in 0..2 }:
> INVENT_1a etc
>
> and
> inventory_1b{x in Xb, y in Y, t in 3..20}:
> INVENT_1b etc
>
> This would get messy in my model.
>
> Can anyone think of any other approaches?
>
May be like this:
inventory_1{x in X, y in Y, t in 0..20}:
INVENT_1[x,y,t] = sum{ (i,j) in set_1 :
(if i <= 2 then attribute_1[i] else 0) = x and
(if i <= 2 then attribute_2[i] else 0) = y } d[t]*x[i,j];
Please note that 'else 0' may be omitted.
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