Genetic algorithm optimization and blending of composite laminates by locally reducing laminate thickness

• Published in: Advances in engineering software (1992) Vol. 35; no. 1; pp. 35 - 43
• Main Authors: Adams, David B., Watson, Layne T., Gürdal, Zafer, Anderson-Cook, Christine M.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2004
• Subjects: Blending; Combinatorial optimization; Composite laminates; Decomposition; Genetic algorithms; Parallel computing; Composite laminates; Parallel computing; Decomposition; Blending; Combinatorial optimization; Genetic algorithms
• ISSN: 0965-9978
• DOI: 10.1016/j.advengsoft.2003.09.001

Composite panel structure optimization is commonly decomposed into panel optimization subproblems, with specified local loads, resulting in manufacturing incompatibilities between adjacent panel designs. A new method proposed here for constructing globally blended panel designs uses a parallel decomposition antithetical to that of earlier work. Rather than performing concurrent panel genetic optimizations, a single genetic optimization is conducted for the entire structure with the parallelism solely within the fitness evaluations. A genetic algorithm approach, based on locally reducing a thick (guide) laminate, is introduced to exclusively generate and evaluate valid globally blended designs, utilizing a simple master–slave parallel implementation, implicitly reducing the size of the problem design space and increasing the quality of discovered local optima.