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For that purpose a genetic algorithm is used, possibly giving different connections with each run.
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For comparison purposes, a Genetic Algorithm (GA) approach is also included to deal with the formulated optimization problem.
For this purpose, a genetic-algorithm-based ordinary kriging with moving neighborhood technique is proposed.
For this purpose, we used a genetic algorithm (GA) that considered the experimental results of a CM wall.
Evolutionary methods have also been employed for this purpose, such as a genetic algorithm [9], particle swarm optimization (PSO) [10], simulated annealing [11], artificial immune system [12], differential evolution [13], and the frog algorithm [14].
In fact, the main purpose of implementing a genetic algorithm is to determine the rules of designing fuzzy-based control approach in such a way that the control does not need information of the expert and be able to work, efficiently.
The design of a genetic algorithm based spatially constrained timber harvest scheduling model.
In this study, we employed an advanced global optimisation algorithm known as a genetic algorithm, a general-purpose, stochastic search and optimisation procedure, based on genetic and evolutionary principles [24].
For this purpose, a framework for optimization-based molecular design is introduced based on property predictions by COSMO-RS and a genetic algorithm for molecular design.
The foundations and implementation of a genetic algorithm (GA) for instrumentation purposes are presented in this paper.
A genetic algorithm and a finite element programme are used for this purpose.
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