Mechanics of Advanced Materials and Structures · 1994 · 90 citations · 10 references
ArchitectureComputational EngineeringDesignComputer-aided DesignDesign OptimizationEvolutionary DesignComposite Structure AnalysisDesign For StrengthEvolutionary OptimizationGenetic AlgorithmsOptimization-based DesignStructural OptimizationBuckling Of Composite LaminatesComposite Laminate DesignComposite Structural DesignGenetic Algorithm Based DesignGenetic Algorithm OptimizationGenetic Algorithms For DesignGenetic Algorithms For SearchPopulation Based Design Optimization
Abstract This paper describes the use of a genetic algorithm with memory for the design of minimum thickness composite laminates subject to strength, buckling and ply contiguity constraints. A binary tree is used to efficiently store and retrieve information about past designs. This information is used to construct a set of linear approximations to the buckling load in the neighbourhood of each member of the population of designs. The approximations are then used to seek nearby improved designs in a procedure called local improvement. The paper demonstrates that this procedure substantially reduces the number of analyses required for the genetic search. The paper also demonstrates that the use of genetic algorithms helps find several alternative designs with similar performance, thus giving the designer a choice of alternatives.
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Genetic algorithms in search, optimization, and machine learning
Choice Reviews Online · 1989 · 49.3K citations