摘要
为了实现企业在云制造环境下的节能,提出一种新的云制造服务组合优化方法,该方法既能降低能耗,又能在考虑不确定性的情况下提高服务质量。然后利用双目标模型和改进的NSGA-Ⅱ解决制造服务组合优化问题。实例研究结果表明:该模型从云制造服务平台(CMSP)的角度有效地控制了能耗,改进后的NSGA-Ⅱ在解决该问题上具有与MOPSO和标准的NSGA-Ⅱ相比的准确性和收敛性优势。
In order to realize the enterprise′s energy saving in cloud manufacturing environment,a novel manufacturing service composition optimization method was presented in this paper to reduce the energy consumption and improve the Quality of Service(QoS)with flexible factors at the same time.Then the bi-objectives model and the improved Non-dominated Sorting Genetic AlgorithmⅡ(NSGA-Ⅱ)were used to solve the manufacturing service composition optimization problem.The result of the case study proves that the proposed model is valid on the control of the energy consumption effectively from the cloud manufacturing service platform(CMSP)position,and the improved NSGA-Ⅱhas the accuracy and convergence advantages on solving the proposed problems comparing with Multi-objectives Particle Swarm Optimization(MOPSO)method and the standard NSGA-Ⅱ.
作者
杨欣
曾珍香
夏玉雄
YANG Xin;ZENG Zhenxiang;XIA Yuxiong(Zhonghuan Information College Tianjin University of Technology,Tianjin 300380,China;School of Economics and Management,Hebei University of Technology,Tianjin 300401,China;Fujian Huading Intelligent Manufacturing Technology Ltd.Company,Fuzhou 350000,China)
出处
《工业工程与管理》
CSSCI
北大核心
2020年第2期164-171,163,共9页
Industrial Engineering and Management
基金
国家社科基金项目《基于云制造模式的供应链环境协同治理研究》(17BGL009)。
关键词
云制造
服务组合优化
能耗
改进的NSGA-Ⅱ
cloud manufacturing
service composition optimization
energy consumption
the improved NSGA-Ⅱ
