Journal of Systems Engineering and Electronics ›› 2026, Vol. 37 ›› Issue (3): 921-932.doi: 10.23919/JSEE.2024.000012

• SYSTEMS ENGINEERING • Previous Articles     Next Articles

Combat task-oriented weapon portfolio selection method

Renqi ZHU1(), Yulong DAI1,*(), Yijun DONG2(), Jiaqing LI3(), Nannan ZHANG4(), Zhiran QIU3()   

  1. 1College of Systems Engineering, National University of Defense Technology, Changsha 410000, China
    2Department of Military and Political Training, Special Police College of China, Beijing 100000, China
    3College of Military and Political Basic Education, National University of Defense Technology, Changsha 410000, China
    4Pearl River College, Tianjin University of Finance and Economics, Tianjin 300345, China
  • Received:2022-11-11 Online:2026-06-18 Published:2026-06-29
  • Contact: Yulong DAI E-mail:zhurenqi@163.com;yulongdai_nudt@nudt.edu.cn;850597566@qq.com;2970453506@qq.com;zhangnankexin@163.com;2924078853@qq.com
  • Supported by:
    This work was supported by the National Natural Science Foundation of China(72204028; 72231011).

Abstract:

Existing weapon portfolio selection methods do not sufficiently support specific combat tasks, with uncertainty in the decision information. Therefore, a combat task–oriented weapon portfolio selection method that adapts weapon capabilities to combat tasks is proposed. The approach is based on specific combat tasks and weapon background, using fuzzy interval values to describe indicators and the applicability of a weapon portfolio. In addition, an interval entropy weighting method is applied to obtain weight information of indicators. Meanwhile, we define the similarity measure of fuzzy interval values and use the interval fuzzy collaborative filtering algorithm to calculate the fitness of the residual weapons. Furthermore, the interval fuzzy set clustering algorithm clusters the tasks to inform the decision of weapon portfolio. Finally, we verify the method’s feasibility and advancement by comparing actual combat tasks as examples with the traditional methods. The contributions of this paper include improvements to the accuracy and reliability of decision-making from the perspective of adapting weapon capability to combat tasks. At the same time, this paper accounts for the method’s shortcomings by considering the hesitancy and ambiguity of the indicator data.

Key words: weapon portfolio selection, interval-value hesitation fuzzy theory, collaborative filtering algorithm, entropy weighting method