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The results of model indicate that optimal updating coefficient obtained by genetic algorithm increases the accuracy of estimation significantly.
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By performing a step by step design process, the multi-stage interactive genetic algorithm increases the focus of user on a component at each stage of the design.
We clearly show that results obtained by Genetic Algorithm with increasing population is better than so far best technique which is really difficult for future researchers to beat.
Variable population size strategy adopted by genetic algorithm can prevent premature convergence by increasing or decreasing the population size when the optimal energy is very close to the average value of the population [ 22].
Then, an algorithm designed by Genetic Algorithm (GA) is used for solving the model.
Layup optimization of the maximum strength of laminated composites with internal ply-drops is performed by genetic algorithm (GA).
OD adaptation algorithm was adjusted to calculate optimum coefficients of characteristic equations by genetic algorithm.
At last, the system was optimized by genetic algorithm.
At last the system has been optimized by genetic algorithm.
Such design problem can be solved by genetic algorithm.
This repeated process is implemented by genetic algorithm.
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