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Optimization of Shape, Size, and Topology Design Variables in Trusses with a Genetic Algorithm Optimization of Shape, Size, and Topology Design Variables in Trusses with a Genetic Algorithm

by Gillman, Kevin M

Abstract (Summary)
Briggs’ genetic algorithm was extended in the Gillman algorithm to include shape optimization of trusses. Other contributions include value representation, different member linking, alternate genes, automatic k-factor evaluation for buckling, and the option to prevent overlapping members. The purpose of these contributions was to make optimization using a genetic algorithm more accessible to design engineers. The Gillman algorithm was demonstrated in two original examples as well as an example from a published work. The Gillman algorithm was effective in finding lighter designs.
Bibliographical Information:

Advisor:

School:Brigham Young University

School Location:USA - Utah

Source Type:Master's Thesis

Keywords:structural optimization shape size topology genetic algorithm truss

ISBN:

Date of Publication:12/08/2004

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