矩形件优化排样是一个NPC问题，在工业界有着广泛的应用．针对该问题，提出一种自适应模拟退火遗传算法．采用一种基于环形交叉算子和环形变异算子的自适应遗传算法来自动调整交叉和变异概率；同时引入模拟退火算法对个体适应度大于平均适应度的个体进行退火处理．自适应模拟退火遗传算法充分发挥了自适应遗传算法与模拟退火算法各自的全局搜索能力与局部搜索能力．对比实验表明，该算法结合改进的最左最下布局算法解决矩形件优化排样问题更加有效．-Optimal layout is rectangular pieces of a NPC problem, in the industrial sector has a wide range of applications. For this problem, an adaptive simulated annealing genetic algorithm. Using a ring-based crossover operator and mutation operator ring adaptive genetic algorithm to automatically adjust the crossover and mutation　and introduce simulated annealing is greater than the average fitness of the individual fitness of individuals annealing. Adaptive simulated annealing genetic algorithm fully adaptive genetic algorithm and simulated annealing their global search capability and local search capabilities. Comparative experiments show that the algorithm is left with the most improved layout algorithm to solve the most under the optimal nesting rectangular pieces of the problem more effectively.