Stacking sequence design of a composite laminate with a given set of plies
is a combinatorial problem of seeking an optimal permutation. Permutation g
enetic algorithms optimizing the stacking sequence of a composite laminate
for maximum buckling load are studied. A new permutation GA named gene-rank
GA is developed and compared with an existing Partially Mapped Permutation
GA, originally developed for solving the travelling salesman problem. The
two permutation GAs are also compared with a standard non-permutation GA. I
t is demonstrated through examples that the permutation GAs are more effici
ent for slacking sequence optimization than a standard GA. Repair strategie
s for standard GA and the two permutation GAs for dealing with constraints
are also developed. It is shown that using repair can significantly reduce
computation cost for both standard GA and permutation GA. (C) 2000 Elsevier
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