Permutation genetic algorithm for stacking sequence design of composite laminates

Stacking sequence design of a composite laminate with a given set of plies is a combinatorial problem of seeking an optimal permutation. Permutation genetic 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. It is demonstrated through examples that the permutation GAs are more ecient for stacking sequence optimization than a standard GA. Repair strategies for standard GA and the two permutation GAs for dealing with constraints are also developed. It is shown that using repair can signi®cantly reduce computation cost for both standard GA and permutation GA. Ó 2000 Elsevier Science S.A. All rights reserved.