I want to implement constraints which ensures that a value is part of a set of decision variables. So for e.g. let dv[i] be a set of decision variables indexed by i. Say, the domain is restricted between 0-10. I want that it should be ensured that a value 4 (say) is a member of dv.
from ortools.sat.python import cp_model as cp
model = cp.CpModel()
dv = [model.NewIntVar(lb=0, ub=10, name = f"dv[{_+1}]") for _ in range(5)]
# this val should be a member of dv
val = 4
Below is one possible way to ensure that a pre-determined value is a member of decision variables.
from ortools.sat.python import cp_model as cp
model = cp.CpModel()
dv = [model.new_int_var(lb=0, ub=10, name = f"dv[{_+1}]") for _ in range(5)]
val = 4
n = len(dv)
b = [model.new_bool_var(f"b[{i}]") for i in range(n)]
for i in range(n):
model.add((dv[i] == val)).only_enforce_if(b[i])
model.add((dv[i] != val)).only_enforce_if(~b[i])
model.add_bool_or(b)
model.maximize(sum(dv))
solver = cp.CpSolver()
status = solver.solve(model)
print([solver.value(dv[i]) for i in range(5)])
# results in : [10, 10, 10, 10, 4]
# no constraints are imposed to place 4 in any specific position