Stacking sequence optimization of composite laminates for maximum buckling load using permutation search algorithm

Due to the involvement of large number of design variables, it is still one of the key concerns to build an efficient optimization algorithm for the stacking sequence design of composite laminates with various constraints. In this work, the flexural stiffness parameters are expressed in terms of the ply orientations, which helps to formulate the maximum of buckling load factor as a problem of identifying the optimum ply orientation at stacking positions. Afterwards, we suggest a permutation search (PS) algorithm to reduce the evaluations in stacking sequence optimization of composite laminates. In the first stage, permutation operations are sequentially performed for each permutation position, and in the second stage a repair strategy is adopted for overcoming the violation of constraints while maximizing the value of the objective function. A comparison has been performed between the PS and three genetic algorithm (GAs) methods. It has been demonstrated that the number of process analyses for stacking sequence optimization are greatly reduced by the PS algorithm. The novel PS algorithm combined with the modified repair strategy outperforms the studied GA methods for constrained stacking sequence optimization of composite laminate both in computational performance and finding the optimal objective value with high reliability.