A Weapon Assignment Algorithm for Rapid Reaction in Multi-Target and Multi-Weapon Environments

다표적-다무장 환경에서 신속 대응을 위한 무장 할당 알고리즘

  • Received : 2018.07.10
  • Accepted : 2018.07.30
  • Published : 2018.08.28


In order to dominate the multiple-targets of high threat in the initial stage of combat, it is necessary to maximize the combat effect by rapidly firing as many weapons as possible within a short time. Therefore, it is mandatory to establish the effective weapon allocation and utilize them for the combat. In this paper, we propose a weapon assignment algorithm for rapid reaction in multi-target and multi-weapon environments. The proposed algorithm maximizes the combat effect by establishing the fire plan that enables the rapid action with the operation of low complexity. To show the superiority of our algorithm, we implement the evaluation and verification of performances through the simulation and visualization of our algorithm. Our experimental results show that the proposed algorithm perform the effective weapon assignment, which shows the high target assignment rate within the fast hour even under the large-scale battle environments. Therefore, our proposed scheme are expected to be highly useful when it is applied to real weapon systems.


Weapon Assignment;Fire Plan;Azimuth;Threat Value


  1. M. Azak and A. Bayrak, "A New Approach for Threat Evaluation and Weapon Assignment Problem, Hybrid Learning with Multi-Agent Coordination," Proc. of the International Symposium on Computer and Information Sciences, pp.1-6, 2008.
  2. S. Sivanandam and S. Deepa, Introduction to Genetic Algorithms, Springer, 2009.
  3. P. Li, L. Wu and F. Lu, "A Mutation-Based GA for Weapon-Target Allocation Problem Subject to Spatial Constraints," Proc. of the International Workshop on Intelligent Systems and Applications, pp.1-4, 2009.
  4. G. Shang, Z. Zaiyue, Z. Xiaoru, and C. Cungen, "Immune Genetic Algorithm for Weapon-Target Assignment Problem," Proc. of the Workshop on Intelligent Information Technology Application, pp.145-148, 2017.
  5. K. Doerner, W. Gutjahr, R. Hartl, C. Strauss, and C. Stummer, "Pareto Ant Colony Optimization: A Metaheuristic Approach to Multiobjective Portfolio Selection," Annals of Operations Research, Vol.131, Issue.1-4, pp.79-99, 2004.
  6. Y. Li, Y. Kou, Z. Li, A. Xu, and Y. Chang, "A Modified Pareto Ant Colony Optimization Approach to Solve Biobjective Weapon-Target Assignment Problem," International Journal of Aerospace Engineering, Vol.2017, Article ID.1746124, pp.1-14, 2017.
  7. G. Shang, "Solving Weapon-Target Assignment Problems by a New Ant Colony Algorithm," Proc. of the International Symposium on Computational Intelligence and Design, Vol.2, pp.221-224, 2008.
  8. S. Chen, J. He, and H. Liu, "Realization and Simulation of Parallel Ant Colony Algorithm to Solve WTA Problem," In Proc. of the International Conference on Systems and Informatics, pp.2458-2461, 2012.
  9. J. Zhang and X. Wang, "ACGA Algorithm of Solving Weapon-Target Assignment Problem," Open Journal of Applied Sciences, Vol.2, No.4B, pp.74-77, 2012.
  10. S. Bisht, "Hybrid Genetic-Simulated Annealing Algorithm for Optimal Weapon Allocation in Multilayer Defence Scenario," Defence Science Journal, Vol.54, No.3, pp.395-405, 2004.
  11. 이준복, 다수무장-다수표적에 대한 실시간 동적교전 할당 알고리즘 연구, 한국과학기술원, 2009.
  12., 2018.7.2.