Detail publikačního výsledku

Advanced Genetic Algorithms for Engineering Design Problems

ROUPEC, J.

Originální název

Advanced Genetic Algorithms for Engineering Design Problems

Anglický název

Advanced Genetic Algorithms for Engineering Design Problems

Druh

Článek recenzovaný mimo WoS a Scopus

Originální abstrakt

The study of analogy of the natural evolution and the technical object design dates back more than 50 years. The genetic algorithm (GA) is considered to be a stochastic heuristic (or meta-heuristic) optimisation method. The best use of GA can be found in solving multidimensional optimisation problems, for which analytical solutions are unknown (or extremely complex) and efficient numerical methods are also not known. Genetic algorithms are inspired by adaptive and evolutionary mechanisms of live organisms, but they do not copy the natural process precisely. The paper describes the main terms, principles and original implementation details of GA. The main goal of this paper is to help readers to use proper GAs on the field of technical objects design.

Anglický abstrakt

The study of analogy of the natural evolution and the technical object design dates back more than 50 years. The genetic algorithm (GA) is considered to be a stochastic heuristic (or meta-heuristic) optimisation method. The best use of GA can be found in solving multidimensional optimisation problems, for which analytical solutions are unknown (or extremely complex) and efficient numerical methods are also not known. Genetic algorithms are inspired by adaptive and evolutionary mechanisms of live organisms, but they do not copy the natural process precisely. The paper describes the main terms, principles and original implementation details of GA. The main goal of this paper is to help readers to use proper GAs on the field of technical objects design.

Klíčová slova

genetic algorithm, stochastic heuristic optimisation methods, evolutionary computing, genetic operators

Klíčová slova v angličtině

genetic algorithm, stochastic heuristic optimisation methods, evolutionary computing, genetic operators

Autoři

ROUPEC, J.

Rok RIV

2011

Vydáno

10.03.2011

ISSN

1802-1484

Periodikum

Engineering Mechanics

Svazek

17

Číslo

5/6

Stát

Česká republika

Strany od

407

Strany do

417

Strany počet

11

BibTex

@article{BUT50989,
  author="Jan {Roupec}",
  title="Advanced Genetic Algorithms for Engineering Design Problems",
  journal="Engineering Mechanics",
  year="2011",
  volume="17",
  number="5/6",
  pages="407--417",
  issn="1802-1484"
}