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Cloud manufacturing resources fuzzy classification based on genetic simulated annealing algorithm

机译:基于遗传模拟退火算法的云制造资源模糊分类

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摘要

To solve the problem of fuzzy classification of manufacturing resources in a cloud manufacturing environment, a hybrid algorithm based on genetic algorithm (GA), simulated annealing (SA) and fuzzy C-means clustering algorithm (FCM) is proposed. In this hybrid algorithm, classification is based on the processing feature and attributes of the manufacturing resource; the inner and outer layers of the nested loops are solving it, GA obtains the best classification number in the outer layer; the fitness function is constructed by fuzzy clustering algorithm (FCM), carrying out the selection, crossover and mutation operation and SA cooling operation. The final classification results are obtained in the inner layer. Using the hybrid algorithm to solve 45 kinds of manufacturing resources, the optimal classification number is 9 and the corresponding classification results are obtained, proving that the algorithm is effective.
机译:为了解决云制造环境中制造资源的模糊分类问题,提出了一种基于遗传算法(GA),模拟退火(SA)和模糊C-MEARE聚类算法(FCM)的混合算法。 在这种混合算法中,分类基于制造资源的处理特征和属性; 嵌套环的内层和外层正在解决,GA获得外层中的最佳分类号; 通过模糊聚类算法(FCM)构造的健身功能,进行选择,交叉和突变操作和SA冷却操作。 最终分类结果是在内层中获得的。 使用混合算法来解决45种制造资源,最佳分类号为9,并获得相应的分类结果,证明该算法是有效的。

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