Improved differential evolution algorithm for solving weapon-target assignment problem

被引：1
|
作者：
Wu W. [1 ]
Guo X. [1 ]
Zhou S. [1 ]
Gao L. [1 ]
机构：
[1] Department of Aeronautical Electric Control, Naval Aviation University Qingdao Campus, Qingdao
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2021年 / 43卷 / 04期
关键词：
Differential evolution algorithm; Random neighbourhood; Self-adaptation parameter; Weapon-target assignment (WTA);
D O I：
10.12305/j.issn.1001-506X.2021.04.18
中图分类号：
学科分类号：
摘要：
To solve the problems of the slow convergence rate and the low search efficiency in solving weapon-target assignment (WTA), an improved differential evolution (DE) algorithm is proposed. Firstly, the WTA model is established under the multi-constraint condition, and the dynamic WTA (DWTA) problem is discretized into the static WTA (SWTA) problem. Secondly, the exploration and exploitation capabilities of DE algorithm gorithm are slightly balanced by the random neighborhood-based mutation strategy, and the adaptive parameter setting method based on historical archive is adopted to dynamically update parameters based on "elite" information. Finally, through the comparative experiments with five kinds of variant DE algorithms, the present algorithm is proved to have a high searching accuracy, a fast convergence speed and a strong robustness. © 2021, Editorial Office of Systems Engineering and Electronics. All right reserved.
引用
收藏
页码：1012 / 1021
页数：9
相关论文
共 27 条
  • [1] LEE M Z., Constrained weapon-target assignment: enhanced very large scale neighborhood search algorithm, IEEE Trans.on Systems Man & Cybernetics Part A Systems & Humans, 40, 1, pp. 198-204, (2010)
  • [2] KLINE A, AHNER D, HILL R., The weapon-target assignment problem, Computers & Operations Research, 105, pp. 226-236, (2019)
  • [3] HOSEIN P A, ATHANS M., Some analytical results for the dynamic weapon-target allocation problem, LIPS-P-1944, (1990)
  • [4] LLOYD S P, WITSENHAUSDEN H S., Weapon allocation is NP-complete, Proc.of the IEEE Summer Simulation Conference, pp. 1054-1058, (1986)
  • [5] HOCAOGLU M F., Weapon target assignment optimization for land based multi-air defense systems: a goal programming approach, Computers & Industrial Engineering, 128, pp. 681-689, (2019)
  • [6] YAO Z X, LI M, CHEN Z J, Et al., Mission decision-making method of multi-aircraft cooperatively attacking multi-target based on game theoretic framework, Chinese Journal of Aeronautics, 29, 6, pp. 1685-1694, (2016)
  • [7] KLINE A G, AHNER D K, LUNDAY B J., Real-time heuristic algorithms for the static weapon target assignment problem, Journal of Heuristics, 25, pp. 377-397, (2019)
  • [8] NI M F, YU Z K, MA F, Et al., A Lagrange relaxation method for solving weapon-target assignment problem, Mathematical Problems in Engineering, 4, pp. 1-10, (2011)
  • [9] ZHOU Y L, LI X B, ZHU Y F, Et al., A discrete particle swarm optimization algorithm applied in constrained static weapon-target assignment problem, Proc.of the 12th World Congress on Intelligent Control and Automation, pp. 3118-3123, (2016)
  • [10] SONUC E, SEN B, BAYIR S., A parallel simulated annealing algorithm for weapon-target assignment problem, International Journal of Advanced Computer Science & Applications, 8, 4, pp. 87-92, (2017)
123