A genetic algorithm for the optimization of fiber angles in composite laminates

A genetic algorithm for the optimization of composite laminates is proposed in this work. The well-known roulette selection criterion, one-point crossover operator, and uniform mutation operator are used in this genetic algorithm to create the next population. To improve the hill-climbing capability of the algorithm, adaptive mechanisms designed to adjust the probabilities of the crossover and mutation operators are included, and the elite strategy is enforced to ensure the quality of the optimum solution. The proposed algorithm includes a new operator called the elite comparison, which compares and uses the differences in the design variables of the two best solutions to find possible combinations. This genetic algorithm is tested in four optimization problems of composite laminates. Specifically, the effect of the elite comparison operator is evaluated. Results indicate that the elite comparison operator significantly accelerates the convergence of the algorithm, which thus becomes a good candidate for the optimization of composite laminates.

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