Publication detail

Advanced Genetic Algorithms for Engineering Design Problems

ROUPEC, J.

Original Title

Advanced Genetic Algorithms for Engineering Design Problems

English Title

Advanced Genetic Algorithms for Engineering Design Problems

Type

journal article - other

Language

en

Original Abstract

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.

English abstract

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.

Keywords

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

RIV year

2011

Released

10.03.2011

Pages from

407

Pages to

417

Pages count

11

BibTex


@article{BUT50989,
  author="Jan {Roupec}",
  title="Advanced Genetic Algorithms for Engineering Design Problems",
  annote="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.",
  chapter="50989",
  journal="Engineering Mechanics",
  number="5/6",
  volume="17",
  year="2011",
  month="march",
  pages="407--417",
  type="journal article - other"
}