多目标事务模糊关联聚类的云制造服务组合算法

Service Composition Algorithms in Cloud Manufacturing Based on Fuzzy Correlation Clustering of Multi-Objective Transactions

摘要:

目前的云制造服务组合方法单纯从某个角度研究服务组合问题,对基于多目标事务的云制造服务组合的考虑不足,服务组合质量不高。为实现敏捷、智能、平稳的云制造服务组合,基于开展多目标事务的云模式通用解析、多目标事务模糊关联特征的云模式通用表示、云制造服务组合多目标事务模糊关联聚类算法等方面研究,改进反向学习算法、可替换服务推荐算法、三角模糊函数、非支配排序遗传公式,设计一种敏捷、智能、平稳的云制造服务组合算法。最后,实施实验验证,与传统算法进行性能对比分析。实验结果表明,相比传统算法,该算法组合响应时间短、误差小,且收敛性、敏捷性、智能性、动态演化性、平稳性高。因此,该算法实现了基于多目标事务模糊关联聚类的云制造服务的有效组合,具有较高的应用价值。

Abstract:

Current methods of service composition in cloud manufacturing study only service composition problems from one angle,it is insufficient to considerate service composition in cloud manufacturing based on multi-objective transactions with low service composition quality.To achieve agile, intelligent and stable service composition in cloud manufacturing, with studying general cloud pattern analysis on multi-objective transactions,general cloud pattern expression on fuzzy correlation features of multi-objective transactions, algorithms on fuzzy correlation clustering of multi-objective transactions of service composition in cloud manufacturing,reverse learning algorithms, alternative service recommendation algorithms, trigonometric fuzzy function and undominated ranking genetic formula were improved,and a agile,intelligent and stable algorithm on service composition in cloud manufacturing was designed. Finally,validating experiments were implemented,and performance of this proposed algorithm was analized compared with traditional algorithms.Experimental results showed this algorithm had shorter composition response time, less error and higher astringency,agility,intelligence, dynamic evolution,stability than those of traditional algorithms.Therefore, this proposed algorithm achieves effective service composition in cloud manufacturing based on fuzzy correlation clustering on multi-objective transactions,it has higher utility.