Cloud manufacturing resources fuzzy classification based on genetic simulated annealing algorithm

ABSTRACT

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.

KEYWORDS:

• Cloud manufacturing
• fuzzy C-means clustering algorithm
• fuzzy classification
• genetic algorithm
• hybrid algorithm
• manufacturing resources
• optimization
• simulated annealing

Acknowledgments

This research work was supported by the Nature Science Foundation of China, and the project name is “Research on the theory and method of manufacturability evaluation in cloud manufacturing environment”, no. 51405030; the Youth Science Foundation of Jilin Province, no. 20160520069JH.