Open Access
Issue
MATEC Web Conf.
Volume 128, 2017
2017 International Conference on Electronic Information Technology and Computer Engineering (EITCE 2017)
Article Number 02004
Number of page(s) 5
Section Simulation Model and Algorithm
DOI https://doi.org/10.1051/matecconf/201712802004
Published online 25 October 2017
  1. Yu Lianfei, Liu Jin, Zhang Weiming, et al. Review of Weapon-Target Assignment Problem Algorithm [J]. Mathematics in Practice and Theory, 2016, 46(2): 26–32. [Google Scholar]
  2. Wu Congmeng, Wang Gongbao. Application of Genetic Ant-Colony algorithm in Target Assignment problem [J]. Ordnance Industry Automation, 2014, 33(4): 8–11. [Google Scholar]
  3. Zhang Chunmei, Chen Jie, Xin Bin. A Discrete Differential Evolution Algorithm for the Weapon Target Assignment Problem [J]. Transactions of Beijing Institute of Technology, 2014, 34(3): 289–293. [Google Scholar]
  4. Li Xinran, Fan Yongsheng. An Improved Particle Swarm Algorithm for Weapon Target Assignment Problem Solving [J]. Fire Control & Command Control, 2014, 39(12): 58–61. [Google Scholar]
  5. Wang Wei, Cheng Shuchang, ZHANG Yuzhi. Research on approach for a type of weapon target assignment [J]. Systems Engineering and Electronics, 2008, 30(9): 1708–1711. [Google Scholar]
  6. Yang Shanliang, Huang Jian, Liu Yang, et al. Analysis of Weapon Target Assignment Problem in Joint Fire Strike Solving by Genetic Algorithm [J]. Computer Simulation, 2012, 29(3): 61–63. [Google Scholar]
  7. Wu Kunhong, Zhan Shixian. Optimization for Target Assignment in Fire Strike Based on Distributed Genetic Simulated Annealing Algorithm [J]. Fire Control & Command Control, 2016, 41(3): 89–92. [Google Scholar]
  8. ANGELOV P.P.Optimization in an intuitionistic fuzzy environment [J]. Fuzzy Sets and Systems, 1997, (86): 299–306. [CrossRef] [Google Scholar]
  9. Xu Xiaolai, Lei Yingjie, Dai Wenyi. Weighted Intuitionistic Fuzzy Multi-object Programming Based on Improved Particle Swarm Algorithm [J]. Journal of System Simulation, 2009, 21(11): 3280–3282. [Google Scholar]
  10. LI Kangping, WANG Pengjun, ZHANG Huihong. The Search of the Best Power Polarity of Ternary FPRM Circuit Based on Simulated annealing Genetic Algorithm[J], Journal of Zhejiang University(Science Edition), 2016 43(2): 190–194, 199. [Google Scholar]
  11. Lin Lingjuan, Liu Xiyu. Rapid partical swarm optimization combined simulated annealing algorithm [J]. Computer Engineering and Applications, 2011, 47(8): 27–29. [Google Scholar]
  12. Liu Bo, Wang Ling, Jin Yihui. An effective hybrid PSO-based algorithm for flow shop schedualing with limited buffers [J]. Computers & Operations Reasearch, 2008, 35(9): 2791–2806. [CrossRef] [Google Scholar]
  13. Luan Zhibo, Huang Qitao, Jiang Hongzhou, et al. Mixed application of two learning mechanisms in genetic algorithm [J]. Systems Engineering and Electronic, 2009, 31(8): 1985–1988. [Google Scholar]
  14. Wei Zhen, Wu Lei, Ge Fangzhen, et al. Hybrid PSO Algorithm Based on Memetic Framework [J]. Pattern Recognition and Artificial Intelligence, 2012, 25(2): 213–219. [Google Scholar]
  15. Zhang Xian, Yaofeng Ren, Wang Runpeng. Research on path planning [J]. Journal of China Ordnance search in continuous time optimal adaptive genetic algorithm based on 2015, 36(12): 2386–2395. [Google Scholar]

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