OPTIMIZATION OF LAMINATE STACKING-SEQUENCE FOR BUCKLING LOAD MAXIMIZATION BY GENETIC ALGORITHM

The use of a genetic algorithm to optimize the stacking sequence of a composite laminate for buckling load maximization is studied. Various genetic parameters including the population size, the probability of m utation, and the probability of crossover are optimized by numerical e xperiments. A new genetic operator-permutation-is proposed and shown t o be effective in reducing the cost of the genetic search. Results are obtained for a graphite-epoxy plate, first when only the buckling loa d is considered, and then when constraints on ply contiguity and strai n failure are added. The influence on the genetic search of the penalt y parameter enforcing the contiguity constraint is studied. The advant age of the genetic algorithm in producing several near-optimal designs is discussed.