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The design parameters are varied to obtain different trial solutions.
The method is a Galerkin finite element method in which the space of trial solutions is spanned by asymptotically derived basis functions.
The second strategy is concerned with determining defuzzified centroid value of the noisy fitness samples, instead of their conventional averaging, as the fitness measure of the trial solutions.
The proposed method is capable of solving the plate problems with different boundary conditions via a step-by-step derivation without any trial solutions.
It uses an adaptive mechanism for selecting how new trial solutions are generated, and a chaotic process for adapting parameter values.
The algorithms are based on evolving a set of trial solutions iteratively until an optimum is reached, at which point the experiment ends.
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The Asian factory dutifully implemented one trial "solution" after another.
Levels of glutamate and aspartate were measured before and 72 h after giving the trial solution.
The trial solution is randomly chosen from a combination from the current population, and it is only accepted if it lowers the statistics.
However, it is hard to select the trial solution initially for optimization because the defined objective function has heavily local minima.
First, an adaptive selection of the sample size for the periodic fitness evaluation of a trial solution based on the fitness variance in its local neighborhood is proposed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com