Sentence examples for optimum solution can be from inspiring English sources

According to the result, the total computational cost was drastically reduced while the same optimum solution can be explored as a single-fidelity optimization.

There is no reason to stick to a suboptimal solution for the sake of computing such a solution faster, specially taking into account that in the remote regions that we are considering, the number of combinations to be checked by exhaustive search is relatively low and, therefore, the optimum solution can be found in just a few seconds or minutes according to the simulations carried out.

If a single objective is optimized, the global optimum solution can be found.

Optimum solutions can be then obtained by defining specific objectives; weight loss can be minimized by lowering the value of heat transfer coefficient.

Also, a feasible sub-optimum solution can be obtained by decoupling the operations of power allocation and band scheduling, and that of flow computation, as follows: (1) The power allocation and band scheduling ( P ij m ( q ), x ij m ( q ) ) are obtained from the log relaxed problem with tangential supports.

Solutions can be elusive.

These solutions can be combined.

Hence, Problems (24)–(25) is a standard concave optimization problem [42] and its optimum solution v can be found via Lagrange method as follows.

Our numerical results in Section 6 show that for reasonably sized number of receivers, the optimum solution(s) can be found in a time that is linearly proportional to the total number of packets.

Straightforwardly, the optimum solution of (21) can be given by the eigenvector corresponding to the largest eigenvalue of matrix M 3. Hence, the proposed estimate of the complex weights of the main array can be expressed as follows {widehat{mathbf{w}}}_m=frac{sqrt{N_m}}{leftVert {mathbf{v}}^{mathbf{prime}}rightVert }{mathbf{U}}_1^{mathbf{prime}}{mathbf{v}}^{mathbf{prime}} (24).

and, therefore, the optimum constellation can be approximated with the solution of the following problem: (14).