[1] 王坤峰, 左旺孟, 谭营, 秦涛, 李立, 王飞跃.生成式对抗网络:从生成数据到创造智能.自动化学报, 2018, 44(5): 769-774 doi: 10.16383/j.aas.2018.y000001

Wang Kun-Feng, Zuo Wang-Meng, Tang Ying, Qin Tao, Li Li, Wang Fei-Yue. Generative adversarial networks: from generating data to creating intelligence. Acta Automatica Sinica, 2018, 44(5): 769-774 doi: 10.16383/j.aas.2018.y000001
[2] 柴天佑.自动化科学与技术发展方向.自动化学报, 2018, 44(11): 1923-1930 doi: 10.16383/j.aas.2018.c180252

Chai Tian-You. Development directions of automation science and technology. Acta Automatica Sinica, 2018, 44(11): 1923-1930 doi: 10.16383/j.aas.2018.c180252
[3] Alfred T, Kristofer B, Julien P, Michael L, Charlotta J, Thomas L, Bengt L. An event-driven manufacturing information system architecture for Industry 4.0. International Journal of Production Research, 2017, 55(5): 1297-1311 doi: 10.1080/00207543.2016.1201604
[4] Kuznetsov A P. Decision making in production on the basis of structure strategy theory. Russian Engineering Research, 2017, 37(9): 801-806 doi: 10.3103/S1068798X17090155
[5] Koren Y, Gu X, Guo W. Reconfigurable manufacturing systems: principles, design, and future trends. Frontiers of Mechanical Engineering, 2018, 13(2): 121-136
[6] Nujoom R, Wang Q, Mohammed A. Optimisation of a sustainable manufacturing system design using the multi-objective approach. International Journal of Advanced Manufacturing Technology, 2018, 96(5-8): 2539-2558 doi: 10.1007/s00170-018-1649-y
[7] Klocke K, Arntz K, Heeschen D. Integrative technology chain design for small scale manufacturers. Production Engineering, 2015, 9(1): 109-117 doi: 10.1007/s11740-014-0590-7
[8] Cheng Y, Zhang Y P, Ji P, Xu W J, Zhou Z D, Tao F. Cyber-physical integration for moving digital factories forward towards smart manufacturing: a survey. International Journal of Advanced Manufacturing Technology, 2018, 97(1-4): 1209-1223 doi: 10.1007/s00170-018-2001-2
[9] Li C, Seeram R, Sunpreet S. A review of digital manufacturing-based hybrid additive manufacturing processes. International Journal of Advanced Manufacturing Technology, 2018, 95(5-8): 2281-2300 doi: 10.1007/s00170-017-1345-3
[10] Lu Y Q, Xu X. Resource virtualization: a core technology for developing cyber-physical production systems. Journal of Manufacturing Systems, 2018, 47(4): 128-140 http://www.sciencedirect.com/science/article/pii/S0278612518300657
[11] 李伯虎, 张霖, 任磊, 柴旭东, 陶飞, 王勇智, 等.云制造典型特征、关键技术与应用.计算机集成制造系统, 2012, 18(7): 1345-1356 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jsjjczzxt201207002t

Li Bo-Hu, Zhang Li, Ren Lei, Chai Xu-Dong, Tao Fei, Wang Yong-Zhi, et al. Typical characteristics, technologies and applications of cloud manufacturing. Computer Integrated Manufacturing Systems, 2012, 18 (7): 1345-1356 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jsjjczzxt201207002t
[12] Wang X V, Wang L H, Gördes R. Interoperability in cloud manufacturing: a case study on private cloud structure for SMEs. International Journal of Computer Integrated Manufacturing, 2018, 31(7): 653-663 doi: 10.1080/0951192X.2017.1407962
[13] Li C Y, Guan J H, Liu T T, Ma N, Zhang J. An autonomy-oriented method for service composition and optimal selection in cloud manufacturing. International Journal of Advanced Manufacturing Technology, 2018, 96(5-8): 2583-2604 doi: 10.1007/s00170-018-1746-y
[14] Yin C, Deng P C, Li X B. Intelligent manufacturing mode for sophisticated equipment assembly workshop. Journal of Advanced Manufacturing Systems, 2018, 17(4): 533-549 doi: 10.1142/S0219686718500300
[15] Nouiri M, Bekrar A, Jemai A, Niar S, Ammari A C. An effective and distributed particle swarm optimization algorithm for flexible job-shop scheduling problem. Journal of Intelligent Manufacturing, 2018, 29(3): 603-615 doi: 10.1007/s10845-015-1039-3
[16] Ta Q C, Billaut J C, Bouquard J L. Matheuristic algorithms for minimizing total tardiness in the $m$-machine flow-shop scheduling problem. Journal of Intelligent Manufacturing, 2018, 29(3): 617-628 doi: 10.1007/s10845-015-1046-4
[17] Ding J Y, Song S J, Gupta J, Zhang R, Chiong R, Wu C. An improved iterated greedy algorithm with a Tabu-based reconstruction strategy for the no-wait flow shop scheduling problem. Applied Soft Computing, 2015, 30: 604-613 doi: 10.1016/j.asoc.2015.02.006
[18] Busogi M, Ransikarbum K, Oh Y G, Kim N. Computational modelling of manufacturing choice complexity in a mixed-model assembly line. International Journal of Production Research, 2017, 55(20): 5976-5990 doi: 10.1080/00207543.2017.1319088
[19] Defersha F, Chen M. Mathematical model and parallel genetic algorithm for hybrid flexible flowshop lot streaming problem. The International Journal of Advanced Manufacturing Technology, 2012, 62(1-4): 249-265 doi: 10.1007/s00170-011-3798-0
[20] Karaboga D. A comparative study of artificial bee colony algorithm. Applied Mathematics and Computation, 2009, 214(1): 108-132 http://www.ams.org/mathscinet-getitem?mr=2541051
[21] Pan Q, Ruiz R. An estimation of distribution algorithm for lot-streaming flow shop problems with setup times. OMEGA—International Journal of Management Science, 2012, 40(2): 166-180 doi: 10.1016/j.omega.2011.05.002