In order to reach the optimal solution to the optimization problem (3), the optimal packet combination that an arbitrary device i can generate in the nth transmission is first derived, i.e., the optimal solution to the following problem: (14).
This section illustrates the optimal solution to the optimization problem (3).
The optimal solution to the optimization problem (14) is characterized in the following theorem.
Ideally, the subchannels and power levels must be allocated jointly to achieve the optimal solution to the optimization problem in (6).
From Figures 2 and 3, it is clear that the proposed resource allocation algorithm outperforms Algorithm 4 in [14] and achieves a performance quite close to that of the brute-force search, which always delivers the optimal solution to the optimization problem considered.
Suppose the gSide values for all subgraph patterns are denoted as (q(g_1)le cdots le q(g_m)) in sorted order, then the optimal solution to the optimization problem in Eq. (12) is {mathcal{T}}^*= {cup }_{i=1}^k{g_i} (13).
Step 2. The solution to the optimization problem (12) provides the optimal values of δ i, i = 1, ⋯, 14, i.e.,, which make the constraint ℛ K) ≤ 0 active.
Simulation results show that BBO is a competitive method in determining an optimal solution to the optimization of promising compounds.
That is, if Π is an optimization problem with an instance I, then we want to find S∈Sol(I) that minimizes val(I, S), called an optimal solution to the optimization problem.
The solution to the optimization problem reveals that for both measurement methods an optimal excitation frequency, an optimal inlet volume, and an optimal outlet volume exist.
Artificial bee colony algorithm finds the optimal position of a food source representing a possible solution to the optimization problem.
