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求解矩形件优化排样的自适应模拟退火遗传算法

Optimal Packing of Rectangles with an Adaptive Simulated Annealing Genetic Algorithm

  • 摘要: 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.

     

    Abstract: An adaptive simulated annealing genetic algorithm is presented for the optimal layout problem of rectangles,which is a NP-complete problem and possesses widespread applications in the industry.Adaptive genetic algorithm,which uses circular crossover operator and circular mutation operator,is adopted to change the probability of crossovers and mutations automatically.Simulated annealing algorithm is used to modify the individuals whose fitness values are higher than the average value of the population.The presented hybrid algorithm syncretizes the global search capability of the adaptive genetic algorithm and the local search capability of the simulated annealing algorithm.The comparison results show that the optimal packing of rectangles can be effectively solved by combining the adaptive simulated annealing genetic algorithm with the improved bottom-left algorithm.

     

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