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This is achieved by carefully defining different penalization schemes for different components of the merit function.
It has been designed by using optimization software with an appropriate merit function.
Apart from this, numerical errors of calculation may also influence the convergence of merit function.
Moreover, we design a new descent direction for the merit function in correction phase.
The merit function is the total compliance corresponding to a given single load case.
The method is based on an optimization process that minimizes a proposed merit function.
The results show the proposed merit function leads to about 3.2% increasing in the speedup.
A merit function of coma and optimization method for the wide flat-field holographic concave gratings is proposed.
The first neural network uses the Fischer Burmeister function to achieve an unconstrained minimization with a merit function.
This allows a global minimization of the merit function and a many-fold decrease of the computer run time.
Furthermore, the proposed merit function provides infill characteristics by favoring sampling points that lay farther from existing points.
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