def create_linear_dual(self, c, b, P, d):
'''
Robust constraint:
c^T*w <= b for all P*w <= d
'''
blk = Block()
blk.construct()
n, m = len(P), len(P[0])
# Add dual variables
blk.var = Var(range(n), within=NonNegativeReals)
# Dual objective
blk.obj = Constraint(expr=quicksum(d[j]*blk.var[j]
for j in range(n)) <= b)
# Dual constraints
blk.cons = ConstraintList()
for i in range(m):
lhs = quicksum(P[j][i]*blk.var[j] for j in range(n))
if lhs.__class__ not in native_numeric_types or lhs != 0:
blk.cons.add(lhs == c[i])
return blk
def construct(self, data=None):
Block.construct(self, data)
