I want to investigate whether it is profitable to invest in an additional production facility, and hence I have to account for an capitilization in my objective function.
As such I am wondering if it is possible to, say, if y[t] = 1, then y[g] = 1 for g != t, g > t and where g,t is a subset of the time interval set T.
My first thought was to have:
subject to Constraint1:
y[t] = y[t-1] for all t in T
But that must surely render the solution of y to become the start value in y[0] which is something I obviously do not want.
For clarification. Assume that y[t] is a binary variable whose value is 1 if the investment is undertaken in time t, otherwise 0.
Hope anyone can shed some light into this!
Regards
The constraint y[t] = 1, then y[g] = 1 for g != t, g > t
can be represented in AMPL as something like:
s.t. c{t in T: t != t0}: y[t + 1] >= y[t];
where t0
is the first element of set T
. Note the use of >=
instead of =
. If y[t]
is 1 for some t
, it will drive y
for all subsequent values of t
to 1.