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

Authors
Journal
Advances in Engineering Software
0965-9978
Publisher
Elsevier
Publication Date
Volume
35
Issue
1
Identifiers
DOI: 10.1016/j.advengsoft.2003.09.001
Keywords
  • Composite Laminates
  • Genetic Algorithms
  • Parallel Computing
  • Combinatorial Optimization
  • Decomposition
  • Blending
Disciplines
  • Computer Science
  • Design
  • Mathematics

Abstract

Abstract 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.

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