The last term in the likelihood corresponds to the constraint that (sum _{i=1}^{n} pi _{i} = 1).
where the first and second terms correspond to the cost function and the third term corresponds to the constraint.
It corresponds to the constraint (24) mentioned in Section 2.3, which forces the AFC system matrix to be block-diagonal.
It corresponds to the constraint kin Riff J-k+1in Rhboxbegin{array}{cc}hfill hfill & hfill andknotin Rhboxhfill end{array}.
and the Lagrange multipliers λ, { μ ̲ π ( k ) } and { μ ¯ π ( k ) } mentioned above such that the KKT condition of the problem (9) holds, where the λ corresponds to the constraint ∑ k = 1 K g k s k ≤ P t, and { μ ̲ π ( k ) } and { μ ¯ π ( k ) } correspond to the constraints {s π(k) ≥ 0} and {s π(k) ≤ P π k)}, respectively.
The distributivity principle (A ⦸ B) ⊗ C ⊢ A ⦸ (B ⊗ C), for example, corresponds to the constraint that for every x,y,z,w,v, if we have a configuration R⊗xyz and R⊕vwy, then there exists an alternative internal point t such that R⊕twx and R⊗tvz.
Note that the constraints in (13b) and (13c) correspond to the constraints in (12b) and (12c), respectively.
The first and fourth constraints form the same set of constraints in (7) and correspond to the constraints π ( t ) ∈ Π ( t ∈ T ) in (9).
The optimal time shares τ i ⋆ are therefore easily obtained from the optimal Lagrangian dual variables u k ⋆, k∈{1,…,L}, that correspond to the constraints α≥μ T(p Tx−p (k))+λ T v (k) in the master program.
They correspond to the constraints between the values of the delay parameters of the system.
