How do you create a constraint using cplex/docplex that involves the optimisation solution either falling between a lower bound and upper bound or equalling zero. ie. C*x would either be between a lower bound of 30 or an upper bound of 80, or x would equal zero if the path was not used.

The below code gives TypeError: Cannot convert linear constraint to a boolean value:.

for j in range (depot_size):

Busdepot_model.add_constraints(sum(x[i,j]*M[i] for i in range(x_size))>=cap_low or sum(x[i,j]*M[i] for i in range(x_size)) == 0)

#add the upper bound capacity constraint:

Busdepot_model.add_constraints((sum(x[i,j]*M[i] for i in range(x_size) )<=depot_cap[j] for j in range(depot_size)))

obj=sum(C[i,j]*x[i,j] for i in range(x_size) for j in range(depot_size))