What do you recommend to do in this situation?
I have a set
M consisting of three separate sets of vectors of various size. In other words
M = [m_1, m_2, m_3] where
m_i are vectors of different sizes. For instance
m_1 could be
m_2 = 22:65 and
m_3 = 100:123(these are separate, no intersection in their elements).
with that, there need to have a variable
x[i,j,m] to have some constraints as the following:
# N is a set which contains all net nodes # x,z are variables x[i,j,m] >= z[i,j] for all i,j in N and m in M
Now, we have another variables that are only defined on
y[i,j,m_1]. So, at some points in some constraints, there’s only need to put condition over a subset of
M (not all of its components). Similar to the following:
#I'm not writing like julia-- more like math version sum(x[i,j,m] for i in N) <= y[i, m] for all j in N and m in m_1
I did try to do this by:
@constraint(model, [j in N, m in m_1], sum( x[i,j,m] for i in N) <= y[i, m] )
This is not working though. Do you know how to do this? having a variables that can act both over the whole set
M and also act locally over just
m_1 or just
I’m not sure if the issue is variable either. What I need to find out is that how to have flexible variable
x that can handle
m_1 at the same time.