Genetic Algorithms in Topological Design of Grillage Structures
The present paper describes the use of genetic algorithms (GA’s) in determining the optimal layout and sizing of grillage structures for stress and displacement constraints. The design space for this problem is highly nonconvex, and not readily amenable to traditional methods of nonlinear programming. The approach develops an optimal topology from a set of predefined structural elements so as to satisfy kinematic stability requirements in addition to the usual constraints of structural strength and stiffness. A two-level GA based search is used, wherein the kinematic stability constraints are imposed at one level, followed by the treatment of stress and displacement constraints at a second level of optimization. Since GA’s search for an optimal design from a discrete set of alternatives in the design space, their adaptation in the topological design problem is natural, and is governed only by issues related to computational efficiency. Strategies designed to alleviate the computational requirements of a GA based search are discussed in the paper.
KeywordsGenetic algorithms grillage topological optimization discrete design variables
Unable to display preview. Download preview PDF.
- 6.Rozvany G. I. N., “Optimality Criteria for Grids, Shells and Arches”, in Optimization of Distributed Parameter Problems, eds. E.J. Haug and J. Cea, pp. 112–151, 1981.Google Scholar
- 7.Hajela, P., Lee E., Lin C.-Y., “Genetic Algorithms in Structural Topology Optimization”, presented at NATO Advanced Research Workshop, Sesimbra, Portugal, June 22–28,1992, to be published in Topology Design of Structures, eds. Bendsoe M. P., Mota-Soares C. A., Kluwer Academic, 1992.Google Scholar
- 8.Hajela P., “Genetic Search - An Approach to the Nonconvex Optimization Problem”, AIAA Journal, Vol. 26, No. 7, pp. 205–1210, July 1990.Google Scholar
- 9.Holland J. H., Adaptation in Natural and Artificial Systems, The University of Michigan Press, Ann Arbor, 1975.Google Scholar
- 10.Lin C.-Y., Hajela P., EVOLVE: A Genetic Search Based Optimization Code With Multiple Strategies, proceedings of OPTT93, Computer-Aided Optimum Design of Structures, 7–9 July, Zaragoza, Spain, 1993, pp. 639–654, Elsevier Applied Science, London, eds. Hernandez S., Brebbia C. A.,.Google Scholar