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Both methods converge to the global solution and aim to maximize the convergence speed.
All methods converge to both speakers.
All methods converge to essentially the same values.
The methods converge to the conjugate solution by exchanging boundary conditions at their interface.
It is shown that using different criteria, the optimum shapes obtained by the ESO and the MESO methods converge to the optimum.
Most of the optimizers reach similar optima, but the gradient-based methods converge to more accurate solutions at a much lower computational cost.
Similar(41)
Tables 3 and 4 roughly illustrate that the zeros of the piecewise linear interpolation of θ-methods converge to the corresponding zeros of the exact solution with the order of accuracy 1 ((thetandqfrac{1}{2})) and 2 ((theta=frac{1}{2})), which is in agreement with Theorem��4.6.
Furthermore, it can be shown that whenever the method enters the region of local convergence, the method converges to a full step procedure and thus λ → 1 [ 17, 22, 23].
We assume that the method converges to the exact solution of the problem if there is convergence at all.
The method converges to Pareto-optimal points.
Theoretical results ensure that the proposed method converges to a global minimizer.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com