Genetic creation of 3-dimentional truss structures

Present paper describes the use of a stochastic search procedure that is the bases of genetic algorithms (GAs), in developing near-optimal topologies of load-bearing truss structures. Much work has already been published on the structural optimization of truss topology using genetic algorithms. In most cases these papers express truss topology as a combination of members, and the existence of each member is directly connected to the genetic code. These methods, however, have a weak point. Namely when these method applied to the topology, they might include needless members or those which lie on other members. In addition to these problems, generated structures are not guaranteed to be structurally stable. These problems become more remarkable when the freedom of the problem becomes large. Additionally, the length of chromosome tends to become long. This paper proposes brand-new implements which resolves those problems by expressing the truss topology as a combination of triangles that are joined to each other. A detail of the proposed methodology is presented as well as the results of numerical examples that clearly show effectiveness and efficiency of the present method.