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http://dx.doi.org/10.7234/kscm.2008.21.1.030

Optimal Design of Laminated Stiffened Composite Structures using a parallel micro Genetic Algorithm  

Yi, Moo-Keun (한국과학기술원 기계공학과 항공우주공학)
Kim, Chun-Gon (한국항공우주연구원 추진제어팀)
Publication Information
Composites Research / v.21, no.1, 2008 , pp. 30-39 More about this Journal
Abstract
In this paper, a parallel micro genetic algorithm was utilized in the optimal design of composite structures instead of a conventional genetic algorithm(SGA). Micro genetic algorithm searches the optimal design variables with only 5 individuals. The diversities from the nominal convergence and the re-initialization processes make micro genetic algorithm to find out the optimums with such a small population size. Two different composite structure optimization problems were proposed to confirm the efficiency of micro genetic algorithm compared with SGA. The results showed that micro genetic algorithm can get the solutions of the same level of SGA while reducing the calculation costs up to 70% of SGA. The composite laminated structure optimization under the load uncertainty was conducted using micro genetic algorithm. The result revealed that the design variables regarding the load uncertainty are less sensitive to load variation than that of fixed applied load. From the above-mentioned results, we confirmed micro genetic algorithm as a optimization method of composite structures is efficient.
Keywords
Parallel micro genetic algorithm; Stiffened composite structures; Load uncertainty; Composite structures optimization;
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