Automatic innovative truss design using grammatical evolution
Truss optimization in the field of Structural Engineering is a growing discipline. The application of Grammatical Evolution, a grammar-based form of Genetic Programming (GP), has shown that it is capable of generating innovative engineering designs. Existing truss optimization methods in GP focus pr...
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Published in: | Automation in construction Vol. 39; pp. 59 - 69 |
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Main Authors: | , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Kidlington
Elsevier B.V
01-04-2014
Elsevier |
Subjects: | |
Online Access: | Get full text |
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Summary: | Truss optimization in the field of Structural Engineering is a growing discipline. The application of Grammatical Evolution, a grammar-based form of Genetic Programming (GP), has shown that it is capable of generating innovative engineering designs. Existing truss optimization methods in GP focus primarily on optimizing global topology. The standard method is to explore the search space while seeking minimum cross-sectional areas for all elements. In doing so, critical knowledge of section geometry and orientation is omitted, leading to inaccurate stress calculations and structures not meeting codes of practice. This can be addressed by constraining the optimisation method to only use standard construction elements.
The aim of this paper is not to find fully optimized solutions, but rather to show that solutions very close to the theoretical optimum can be achieved using real-world elements. This methodology can be applied to any structural engineering design which can be generated by a grammar.
•Real-world material stress limits vary according to physical section properties.•Truss optimization using standard elements and design to regulations is introduced.•Minimum achievable weights are considerably higher when codes of practice are adhered to. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 |
ISSN: | 0926-5805 1872-7891 |
DOI: | 10.1016/j.autcon.2013.11.009 |