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The Scientific World Journal
Volume 2014 (2014), Article ID 941532, 21 pages
http://dx.doi.org/10.1155/2014/941532
Research Article

Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization

1Department of Information Service & Intelligent Control, Shenyang Institute of Automation, Chinese Academy of Sciences, Faculty Office VII, Nanta Street No. 114, Dongling District, Shenyang 110016, China
2University of Chinese Academy of Sciences, Beijing 100039, China

Received 22 October 2013; Accepted 4 December 2013; Published 23 January 2014

Academic Editors: T. Chen, Q. Cheng, and J. Yang

Copyright © 2014 Lianbo Ma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [10 citations]

The following is the list of published articles that have cited the current article.

  • Khalid Hasnan, Aftab Ahmed, Badrul-Aisham, Qadir Bakhsh, Kashif Hussain, and Kamran Latif, “A novel optimal RFID network planning by MC-GPSO,” Indian Journal of Science and Technology, vol. 8, no. 17, 2015. View at Publisher · View at Google Scholar
  • Hou, Li, Deng, and Diao, “Effects of varroa destructor on temperature and humidity conditions and expression of energy metabolism genes in infested honeybee colonies,” Genetics and Molecular Research, vol. 15, no. 3, 2016. View at Publisher · View at Google Scholar
  • Majid Hashmipour, Aydin Azizi, and Ali Vatankhah Barenji, “Optimizing radio frequency identification network planning through ring probabilistic logic neurons,” Advances in Mechanical Engineering, vol. 8, no. 8, pp. 1–12, 2016. View at Publisher · View at Google Scholar
  • Simon Fong, Suash Deb, Thomas Hanne, and Jinyan (Leo) Li, “Eidetic Wolf Search Algorithm with a Global Memory Structure,” European Journal of Operational Research, 2016. View at Publisher · View at Google Scholar
  • Shin-Yeu Lin, and Hsing-Fang Tsai, “Micro genetic algorithm with spatial crossover and correction schemes for constrained three-dimensional reader network planning,” Expert Systems With Applications, vol. 44, pp. 344–353, 2016. View at Publisher · View at Google Scholar
  • Shikai Jing, Xiaodan Lian, Hanning Chen, Tao Zou, and Lianbo Ma, “Optimal layout and deployment for RFID system using a novel hybrid artificial bee colony optimizer based on bee life-cycle model,” Soft Computing, 2016. View at Publisher · View at Google Scholar
  • Khalid Hasnan, Aftab Ahmed, Badrul-Aisham, Kamran Latif, Qadir Bakhsh, and Kashif Hussain, “Integration of RFID network planning with XBee network: A new approach,” International Journal of Smart Home, vol. 10, no. 4, pp. 325–334, 2016. View at Publisher · View at Google Scholar
  • Xianghua Fang, Zhengwu Wang, Chunxiu Wang, Jian Wu, Ya Yang, Fang Li, Yang Hua, Dachuan Liu, Yanning Cai, Rong Wang, and Shaochen Guan, “Cardiovascular and Cognitive Health Study in Middle-Aged and Elderly Residents of Beijing (CCHS-Beijing): Design and Rationale,” Neuroepidemiology, vol. 46, no. 3, pp. 182–190, 2016. View at Publisher · View at Google Scholar
  • Atef Jaballah, and Aref Meddeb, “A new variant of cuckoo search algorithm with self adaptive parameters to solve complex RFID network planning problem,” Wireless Networks, 2017. View at Publisher · View at Google Scholar
  • Aydin Azizi, “Introducing a novel hybrid artificial intelligence algorithm to optimize network of industrial applications in modern manufacturing,” Complexity, vol. 2017, 2017. View at Publisher · View at Google Scholar