A computer-based, interactive genetic algorithm optimisation design tool (GENOD) for reinforced concrete structures

Hdl Handle:
http://hdl.handle.net/10545/582942
Title:
A computer-based, interactive genetic algorithm optimisation design tool (GENOD) for reinforced concrete structures
Authors:
Ceranic, Boris; Fryer, Colin
Abstract:
This paper describes the application of genetic algorithms to the optimum cost design of realistic reinforced concrete structures, set within an artificial intelligence computer design environment. The interactive optimisation design tool GENOD developed by authors combines structural analysis with design and offers advantages over the current use of computer technology in design offices. Traditional design of reinforced concrete structures requires the adherence to precise guidelines as specified in the relevant Codes of Practice. This process relies on the designer's intuition and experience and often it is not clear which direction will lead towards a more economical structure. GENOD, however, replaces this conventional approach by a systematic, goal-orientated design process that uses artificial intelligence in searching and sorting through similar design concepts to achieve an economical design. Genetic algorithms are implemented using an object-orientated visual programming language offering facilities for continual monitoring, assessing and changing the current state of the search control parameters. These facilities are shown to be essential when determining the most suitable control parameter settings for a given structural problem. Results obtained so far have shown that genetic algorithms can be successfully applied to the minimum cost design of reinforced concrete skeletal structures, overcoming the difficulties associated with the practical assessment of the structural costs, discontinuity of the design equations and their complex interrelationship with the design variables.
Affiliation:
University of Derby
Citation:
Ceranic, B. and Fryer, C., (2000), ‘A computer-based, interactive genetic algorithm optimisation design tool (GENOD) for reinforced concrete structures’, International Journal of Design Computing, Vol. 2, ISSN 1329-7147
Journal:
International Journal of Design Computing, Vol. 2
Issue Date:
Jan-2000
URI:
http://hdl.handle.net/10545/582942
Type:
Article
Language:
en
ISSN:
1329-7147
Appears in Collections:
The Built Environment Research Group (BERG)

Full metadata record

DC FieldValue Language
dc.contributor.authorCeranic, Borisen
dc.contributor.authorFryer, Colinen
dc.date.accessioned2015-11-30T14:06:05Zen
dc.date.available2015-11-30T14:06:05Zen
dc.date.issued2000-01en
dc.identifier.citationCeranic, B. and Fryer, C., (2000), ‘A computer-based, interactive genetic algorithm optimisation design tool (GENOD) for reinforced concrete structures’, International Journal of Design Computing, Vol. 2, ISSN 1329-7147en
dc.identifier.issn1329-7147en
dc.identifier.urihttp://hdl.handle.net/10545/582942en
dc.description.abstractThis paper describes the application of genetic algorithms to the optimum cost design of realistic reinforced concrete structures, set within an artificial intelligence computer design environment. The interactive optimisation design tool GENOD developed by authors combines structural analysis with design and offers advantages over the current use of computer technology in design offices. Traditional design of reinforced concrete structures requires the adherence to precise guidelines as specified in the relevant Codes of Practice. This process relies on the designer's intuition and experience and often it is not clear which direction will lead towards a more economical structure. GENOD, however, replaces this conventional approach by a systematic, goal-orientated design process that uses artificial intelligence in searching and sorting through similar design concepts to achieve an economical design. Genetic algorithms are implemented using an object-orientated visual programming language offering facilities for continual monitoring, assessing and changing the current state of the search control parameters. These facilities are shown to be essential when determining the most suitable control parameter settings for a given structural problem. Results obtained so far have shown that genetic algorithms can be successfully applied to the minimum cost design of reinforced concrete skeletal structures, overcoming the difficulties associated with the practical assessment of the structural costs, discontinuity of the design equations and their complex interrelationship with the design variables.en
dc.language.isoenen
dc.subjectReinforced concreteen
dc.subjectGenetic Algorithmsen
dc.subjectOptimisationen
dc.subjectStructural designen
dc.titleA computer-based, interactive genetic algorithm optimisation design tool (GENOD) for reinforced concrete structuresen
dc.typeArticleen
dc.contributor.departmentUniversity of Derbyen
dc.identifier.journalInternational Journal of Design Computing, Vol. 2en
All Items in UDORA are protected by copyright, with all rights reserved, unless otherwise indicated.