Acta Metallurgica Sinica(English letters) ›› 2015, Vol. 22 ›› Issue (3): 92-99.doi: 10.1016/S1005-8885(15)60657-4

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Hamming-distance-based adaptive quantum-inspired evolutionary algorithm for network coding resources optimization

Qu Zhijian, Liu Xiaohong, Zhang Xianwei, Xie Yinbao, Li Caihong   

  1. School of Computer Science and Technology, Shandong University of Technology
  • 收稿日期:2014-09-24 修回日期:2014-11-21 出版日期:2015-06-30 发布日期:2015-06-24
  • 通讯作者: Li Caihong, E-mail: handuhandu@163.com E-mail:handuhandu@163.com
  • 基金资助:
    the National Natural Science Foundation of China (61473179), the Doctor Foundation of Shandong Province (BS2013DX032), the Youth Scholars Development Program of Shandong University of Technology (2014-09)

Hamming-distance-based adaptive quantum-inspired evolutionary algorithm for network coding resources optimization

Qu Zhijian, Liu Xiaohong, Zhang Xianwei, Xie Yinbao, Li Caihong   

  1. School of Computer Science and Technology, Shandong University of Technology
  • Received:2014-09-24 Revised:2014-11-21 Online:2015-06-30 Published:2015-06-24
  • Contact: Li Caihong, E-mail: handuhandu@163.com E-mail:handuhandu@163.com
  • Supported by:
    the National Natural Science Foundation of China (61473179), the Doctor Foundation of Shandong Province (BS2013DX032), the Youth Scholars Development Program of Shandong University of Technology (2014-09)

摘要: An adaptive quantum-inspired evolutionary algorithm based on Hamming distance (HD-QEA) was presented to optimize the network coding resources in multicast networks. In the HD-QEA, the diversity among individuals was taken into consideration, and a suitable rotation angle step (RAS) was assigned to each individual according to the Hamming distance. Performance comparisons were conducted among the HD-QEA, a basic quantum-inspired evolutionary algorithm (QEA) and an individual’s fitness based adaptive QEA. A solid demonstration was provided that the proposed HD-QEA is better than the other two algorithms in terms of the convergence speed and the global optimization capability when they are employed to optimize the network coding resources in multicast networks.

关键词: network coding, quantum-inspired evolutionary algorithm, Hamming distance, multicast network

Abstract: An adaptive quantum-inspired evolutionary algorithm based on Hamming distance (HD-QEA) was presented to optimize the network coding resources in multicast networks. In the HD-QEA, the diversity among individuals was taken into consideration, and a suitable rotation angle step (RAS) was assigned to each individual according to the Hamming distance. Performance comparisons were conducted among the HD-QEA, a basic quantum-inspired evolutionary algorithm (QEA) and an individual’s fitness based adaptive QEA. A solid demonstration was provided that the proposed HD-QEA is better than the other two algorithms in terms of the convergence speed and the global optimization capability when they are employed to optimize the network coding resources in multicast networks.

Key words: network coding, quantum-inspired evolutionary algorithm, Hamming distance, multicast network