基于可用性分析的制造云服务组合优化  

Manufacturing Cloud Service Composition Optimization Based on Usability Analysis

作　　者：徐斌[1] 吕佳祺 刘舰 胡钢[1] 张洪亮[1] 潘瑞林[1] XU Bin;LV Jiaqi;LIU Jian;HU Gang;ZHANG Hongliang;PAN Ruilin(School of Management Science and Engineering,Anhui University of Technology,Maanshan,Anhui 243032,China)

机构地区：[1]安徽工业大学管理科学与工程学院,安徽马鞍山243032

出　　处：《工业工程与管理》2024年第3期1-11,共11页Industrial Engineering and Management

基　　金：国家自然科学基金资助项目(7177020917);安徽省自然科学基金项目(2108085MG236,2208085MG181);安徽省高校自然科学研究重点项目(2022AH050324)。

摘　　要：云制造是信息化和智能化背景下新型制造资源的组织形式,已在国内外研究应用,具有广阔的发展前景。制造云服务组合优化是其中一项关键技术,直接决定了云制造服务的质量和效率。从服务的可用性研究出发,首先给出制造云服务组合可用性的定义,然后从有效性、效率和满意度三个方面展开,构建了可用性分析的指标体系,并在此基础上建立了一种新的制造云服务组合多目标优化模型。在求解算法方面,提出了一种改进的NSGA-Ⅲ算法,该算法继承了差分进化算法和遗传K均值聚类算法的优点,改善了原算法的搜索效率和收敛性。最后通过算法测试比较及实例模拟,验证了所提模型与算法的可行性和高效性。Cloud manufacturing is a new form of manufacturing resource organization under the background of informatization and intelligence.It has been studied and applied at home and abroad and has broad development prospects.Manufacturing cloud service composition optimization is one of the key technologies,which directly determines the quality and efficiency of cloud manufacturing services.Starting from the research of service usability,the definition of manufacturing cloud service composition usability was given.According to the definition,the usability analysis indicator system was constructed from effectiveness,efficiency and satisfaction.A new multi-objective optimization model of manufacturing cloud service composition was established.Furthermore,an improved NSGA-II algorithm was proposed,which inherited the advantages of differential evolution algorithm and genetic K-means clustering algorithm,and improved the search efficiency and convergence of the original algorithm.The feasibility and efficiency of the proposed model and algorithm were proved by the algorithm test and manufacturing task simulation.

关 键 词：云制造 制造云服务 可用性分析 服务组合优化 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]