Advanced genetic algorithms for engineering design problems

Title:

Advanced genetic algorithms for engineering design problems

Creator:

Roupec, Jan

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:88215388-464f-4020-a212-7640a59d35b5
uuid:88215388-464f-4020-a212-7640a59d35b5

Subject:

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

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

The study is 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. GAs 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 object design. and Obsahuje seznam literatury

Language:

English

Rights:

http://creativecommons.org/licenses/by-nc-sa/4.0/
policy:public

Coverage:

407-417

Source:

Engineering mechanics: international journal for theoretical and applied mechanics | 2010 Volume:17 | Number:5-6

Harvested from:

CDK

Metadata only:

false