Open Access
Issue
MATEC Web of Conferences
Volume 42, 2016
2015 The 3rd International Conference on Control, Mechatronics and Automation (ICCMA 2015)
Article Number 04004
Number of page(s) 5
Section Machinery manufacturing and industrial applications
DOI https://doi.org/10.1051/matecconf/20164204004
Published online 17 February 2016
  1. Wu, Yu, Xiao-dong Xu, and Cong-xin Li. Modeling research on manufacturing execution system based on large-scale system cybernetics. Journal of Shanghai Jiaotong University (Science) 13 (2008) 744–747. [CrossRef] [Google Scholar]
  2. Wong, Wing-Keung, Z. X. Guo, and S. Y. S. Leung. Intelligent multi-objective decision-making model with RFID technology for production planning. International Journal of Production Economics 147 (2014) 647–658. [CrossRef] [Google Scholar]
  3. Zhang, Yingfeng, et al. Implementation of real-time shop floor manufacturing using RFID technologies. International Journal of Manufacturing Research 5.1 (2009) 74–86. [CrossRef] [Google Scholar]
  4. Sheng, Leng, Cuihua Chao, Fanglin Zou and Zhi Nie. Development on smart data collection and management in workshop based on the internet of things. International Conference on Communication Software and Networks (ICCSN). IEEE, (2015) 272–276. [Google Scholar]
  5. Wei, Zhou, Bu Yan-ping, and Zhou Ye-qing. An improved genetic algorithm for solving flexible job shop scheduling problem. Control and Decision Conference (CCDC), 2013 25th Chinese. IEEE, (2013) 4553–4558. [CrossRef] [Google Scholar]
  6. Gen, Mitsuo, Jie Gao, and Lin Lin. Multistage-based genetic algorithm for flexible job-shop scheduling problem. Intelligent and evolutionary systems. Springer Berlin Heidelberg, (2009) 183–196. [CrossRef] [Google Scholar]
  7. Farashahi, Hamid Ghaani, et al. Efficient Genetic Algorithm for Flexible Job-Shop Scheduling Problem Using Minimise Makespan. Intelligent Computing and Information Science. Springer Berlin Heidelberg, (2011) 385–392. [CrossRef] [Google Scholar]
  8. Chaudhry, I. A. Job shop scheduling problem with alternative machines using genetic algorithms. Journal of Central South University 19.5 (2012) 1322–1333. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.