Genetic algorithm is applicable to optimization of composite laminated panel, but its efficiency is rather low. We aim to raise its efficiency. Our proposed method, by means of analyzing the effects of probabilities of crossover and mutation on convergence of genetic algorithm, can accelerate the evolution process by changing the probabilities of crossover and mutation automatically in accordance with the fitness of each individual. Furthermore, an effective multilevel optimization method is adopted. In system level optimization, the optimum geometrical factors and structural dimension are obtained by the mathematical programming technique. In component level optimization, the practical stacking sequence to realize the given geometrical factors is searched by the adaptive genetic algorithm. The numerical results of two illustrative examples are given in Figs. 1 and 2, where the upper curves correspond to standard genetic algorithm and the lower curves correspond to our adaptive genetic algorithm. Figs.1 and 2 show th at our proposed adaptive genetic algorithm has an efficiency superior to that of standard genetic algorithm.%分析了杂交概率和突变概率对遗传算法收敛性的影响，提出了一种自适应遗传算法，并利用 该方法研究了复合材料层合板的铺层顺序优化设计问题。算例结果表明，提出的复合材料层 合板铺层顺序优化设计方法能够明显地提高计算效率。
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