DESIGN OF COMPOSITE LAMINATES BY A GENETIC ALGORITHM WITH MEMORY

Publisher Website
Google Scholar
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.

This publication has 0 references indexed in Scilit: