基于生成对抗网络的云制造工业服务选择方法  

Selection Method for Cloud Manufacturing Industrial Services Based on Generative Adversarial Networks

作　　者：郑秀宝 李静[1] 祝铭 宁莹莹 ZHENG Xiubao;LI Jing;ZHU Ming;NING Yingying(School of Computer Science and Technology,Shandong University of Technology,Zibo,Shandong 255000,China)

机构地区：[1]山东理工大学,山东淄博255000

出　　处：《计算机科学》2025年第4期54-63,共10页Computer Science

基　　金：国家留学基金管理委员会“促进与加拿大、澳大利亚、新西兰及拉美地区科研合作与高层次人才培养项目”(留美金[2023]21号);教育部高等学校科学研究发展中心中国高校产学研创新基金-新一代信息技术创新项目(2023IT056)。

摘　　要：随着信息技术和制造技术的深度融合,云制造工业生产已成为制造业的关键部分。云制造环境的动态性和服务资源间的相互依赖关系,使得选择最佳工业资源服务变得困难。现有的选择优化方法大多基于启发式算法,但这些算法往往缺乏对云制造环境的自适应能力。因此,文中构建了一种云制造环境下的服务选择模型,提出了一种基于深度学习和生成对抗网络思想的服务选择算法,该模型能够灵活适应环境变化,利用图表示学习方法构建任务服务约束图,根据任务、服务和工业生产约束之间的内在联系学习资源服务特征,在算法改进阶段引入梯度优化和损失函数策略,选择最佳工业资源服务。实验结果表明,所提算法相较于其他对比算法表现出了更强的性能优势。With the deep integration of information technology and manufacturing technology,cloud manufacturing industrial production has become a key part of the manufacturing industry.Due to the dynamics of the cloud manufacturing environment and the interdependencies between service resources,it isn’t easy to select the best industrial resource services.Most of the existing selection optimization methods are based on heuristic algorithms,but these algorithms cannot often adapt to the cloud manufacturing environment.Therefore,this paper constructs a service selection model in the cloud manufacturing environment,proposes a service selection algorithm based on deep learning and generative adversarial network ideas,which can flexibly adapt to environmental changes,uses the graph representation learning method to construct a task service constraint graph,and then learns the characteristics of resource services according to the intrinsic relationship between tasks,services,and industrial production constraints,and introduces gradient optimization and loss function strategies in the algorithm improvement stag and select the best industrial resource services.Experiments show that the proposed algorithm has stronger performance advantages than other comparison algorithms.

关 键 词：云制造 工业生产约束 图表示学习 生成对抗网络 梯度损失函数 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]