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Truss topology optimization by a modified genetic algorithm
This paper describes the use of a stochastic search procedure based on genetic algorithms for developing near-optimal topologies of load-bearing truss structures. Most existing cases these publications express the truss topology as a combination of members. These methods, however, have the disadvantage that the resulting topology may include needless members or those which overlap other members. In addition to these problems, the generated structures are not necessarily structurally stable. A new method, which resolves these problems by expressing the truss topology as a combination of triangles, is proposed in this paper. Details of the proposed methodology are presented as well as the results of numerical examples that clearly show the effectiveness and efficiency of the method.
Truss topology optimization by a modified genetic algorithm
This paper describes the use of a stochastic search procedure based on genetic algorithms for developing near-optimal topologies of load-bearing truss structures. Most existing cases these publications express the truss topology as a combination of members. These methods, however, have the disadvantage that the resulting topology may include needless members or those which overlap other members. In addition to these problems, the generated structures are not necessarily structurally stable. A new method, which resolves these problems by expressing the truss topology as a combination of triangles, is proposed in this paper. Details of the proposed methodology are presented as well as the results of numerical examples that clearly show the effectiveness and efficiency of the method.
Truss topology optimization by a modified genetic algorithm
Kawamura, H. (author) / Ohmori, H. (author) / Kito, N. (author)
Structural and Multidisciplinary Optimization ; 23 ; 467-472
2002
6 Seiten, 9 Quellen
Article (Journal)
English
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