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Given the large number of parameters to configure, on one hand relative to the McGM algorithm, and on the other hand those based on available resources, the use of genetic algorithms (GAs) can be useful to reduce time-consuming exploration.
Levin, M. Use of Genetic Algorithms to solve biomedical Problems.
The first software was Evolver, which is based on the use of genetic algorithms.
This paper describes the use of genetic algorithms to optimize the design and performance of hydrocyclones.
Use of genetic algorithms (GAs) in optimizing such structure consumes significant computational time.
The approach is based on the combined use of Genetic Algorithms and Lyapunov equation solvers.
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The optimization makes use of Genetic Algorithm (GA).
This was achieved by the use of Genetic Algorithm methods to optimize the isolation characteristics of the structure.
The approach also considers the use of genetic algorithm methods to optimize the product configuration in terms of energy efficiency.
This work investigates the use of genetic algorithm to design a multilayer band pass filter in visible range.
The large search space for tuning these parameters has motivated the use of Genetic Algorithm to optimise the solution.
More suggestions(15)
use of randomized algorithms
use of such algorithms
use of metaheuristic algorithms
use of adaptive algorithms
use of specific algorithms
use of intelligent algorithms
use of geoscientific algorithms
use of exact algorithms
use of standard algorithms
use of stochastic algorithms
use of iterative algorithms
use of adequate algorithms
use of multiple algorithms
use of complex algorithms
use of genetic markers
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