Báo Cáo A novel approach for effectively convergent optimisation of genetic algorithms by applying a new acc

ABSTRACT .
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In recent years, genetic algorithm is becoming a powerful tool for researchers and engineers to find good optimal solutions in diverse hard computational mechanical and electrical engineering problems. However, classic genetic algorithms (GA) encounter several disadvantages in which this is the difficulty of choosing optimal parameter settings. Genetic algorithm literature has presented lots of empirical tricks that enable GAs to be convergent better in some way. This paper presents a novel approach for applying a new acceleration technique as well as applying the DeJong functions in testing which has enabled engineers to resolve optimal mechanical and electrical engineering problems that outperform conventional GAs. Thus, the GA with new acceleration technique is experimented in simulation for gathering the simulated data then comparing them with the results from conventional GA. Consequently, a conclusion can be settled on how efficient the new GA proves.

Keywords : genetic algorithm, acceleration technique, optimal control, accelerated genetic algorithm, DeJong function .