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Analysis of features of genetic algorithms

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Hisoblash va amaliy matematika muammolari

Hisoblash va amaliy matematika muammolari

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Currently there is no universal method of optimization, which would allow to solve any problem and uniquely identified as the best among the other methods on the accuracy of the solution. Unlike traditional methods, multivariable optimization, many of which are often characterized by a sharp increase in computational cost as the number of variable parameters, genetic algorithms are well established in large-scale problems. The paper deals with features of genetic algorithms and discusses the problem of modern optimization methods. It is shown that optimization by simulation methods allows to achieve significantly better performance than analytical methods. Describes a modified version of the genetic algorithm to solve problems of multiextremal optimization. Algorithm is tested on the test tasks. The proposed algorithm will be applied researchers in solving applied multiextremal problems where the computation of the objective function requires large computational resources.

AUTHORS

D.Muxamedieva

Toshkent axborot texnologiyalari universiteti

Tags

# оператор# мутация# mutation# селекция# генетический алгоритм# скрещивание# многоэкстремальная оптимизация# genetic algorithm# operator selection# crossover# multiextremal optimization# gеnеtik algoritm# opеrator# sеlеksiya# chatishtirish# mutatsiya# ko’p ekstrеmal optimizatsiya

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Article Identifiers

ROI:

https://eroi.uz/11.0007/A1119-0012

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Not Available

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