非功能属性两阶段制造云服务优选问题研究  

Research on Two-stage Manufacturing Cloud Service Optimization Based on Non-functional Attribute

作　　者：吴英[1] 杨力[1] 赵之元 WU Ying;YANG Li;ZHAO Zhiyuan(Economics Trade and Management College, Anhui Vocational College of Defense Technology, Lu’an 237011, China)

机构地区：[1]安徽国防科技职业学院经贸管理学院,安徽六安2370111

出　　处：《安庆师范大学学报（自然科学版）》2018年第4期35-39,共5页Journal of Anqing Normal University(Natural Science Edition)

基　　金：安徽高校人文社会科学重大研究项目(SK2017A0828);安徽省2016年省级质量工程教学团队项目(2016jxtd025);安徽国防科技职业学院2017年度校级教学研究项目(gf2017jxyjy15)

摘　　要：针对云制造系统中制造云服务优选问题,基于非功能属性研究了包含服务筛选和服务选择的两阶段制造云服务优选方法。以符合用户功能需求的制造云服务为研究对象,基于调度规则筛选快速生成精简的候选云服务集,采用三角模糊数层次分析法和熵值法组合赋权确定权重,并借助TOPSIS决策对候选云服务集实施综合评价,以此选出最佳制造云服务。文中详细阐述了基于调度规则的制造云服务筛选过程,并通过算例验证了基于组合赋权及TOPSIS的制造云服务选择方法的可行性和科学合理性。Aiming at the problem of manufacturing cloud service optimization in cloud manufacturing system,a twostage manufacturing cloud service optimization method including service screening and service selection is studied based on non-functional attributes.The manufacturing cloud service,which is in line with the user's functional requirements,is taken as the research object.In this paper,we firstly propose a cloud filtering method based on scheduling rules.Then we adopt a method of determining the weight of the combination empowerment of the Triangular Fuzzy Number AHP and Entropy Method,and implements the comprehensive evaluation of the Manufacturing Cloud Service with the help of the TOPSIS decision,to select the best manufacturing cloud service.Finally,an example is given to further verify the feasibility and effectiveness of the method.

关 键 词：云制造 制造云服务优选 组合赋权 三角模糊数 TOPSIS 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]