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Journal of Projectiles, Rockets, Missiles and Guidance >

2026 , Vol. 46 >Issue 1: 61 - 76

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2026.01.007

A Target Assignment Method Based on Variable Neighborhood Quantum Particle Swarm Optimization for Heterogeneous Anti-unmanned Equipment Swarms

  • ZHANG Teng 1, 2, 3 ,
  • WANG Zheng , 1, 2, 3, * ,
  • WANG Xuyang 4 ,
  • WU Songsen 1, 5 ,
  • WEI Yali 1, 6 ,
  • WANG Xiaotian 1 ,
  • NING Xin 4 ,
  • CHEN Zhansheng 7
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  • 1 Unmanned Systems Research Institute,Northwestern Polytechnical University,Xi'an 710072,Shaanxi,China
  • 2 National Key Laboratory of Unmanned Aerial Vehicle Technology,Northwestern Polytechnical University,Xi'an 710072,Shaanxi,China
  • 3 Integrated Research and Development Platform of Unmanned Aerial Vehicle Technology,Northwestern Polytechnical University,Xi'an 710072,Shaanxi,China
  • 4 School of Astronautics,Northwestern Polytechnical University,Xi'an 710072,Shaanxi,China
  • 5 Luoyang Institute of Electro-Optical Equipment,Luoyang 471000,Henan,China
  • 6 Shanghai Electro-Mechanical Engineering Institute,Shanghai 201109,China
  • 7 Shanghai Institute of Satellite Engineering,Shanghai 201109,China

Received date: 2025-12-04

  Online published: 2026-03-09

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Abstract

To address the low decision-making efficiency and poor practicality of weapon-target assignment (WTA) in modern air-defense operations,a multi-objective WTA model that comprehensively considers four performance metrics including ammunition consumption,operational cost,total engagement time,and interception benefit is constructed.Practical constraints such as weapon-ammunition compatibility,ammunition inventory,and damage thresholds,etc,are also taken into account to enhance the battlefield applicability of the model.Secondly,a hybrid heuristic algorithm—hybrid ahaotic quantum particle swarm optimization-variable neighborhood search (HCQPSO-VNS) is proposed to solve the proposed WTA model.In the proposed algorithm,a logistic chaotic mapping is employed to improve the quality of the initial population,the quantum particle swarm optimization (QPSO) is utilized for global search; and the variable neighborhood search (VNS) with multiple neighborhood structures is integrated for local optimization to avoid premature convergence.Simulated results demonstrate that the proposed algorithm converges to a high-quality feasible solution within very few iterations.The obtained assignment schemes satisfy the expected lower bounds for damage,weapon-ammunition compatibility,and other constraints,while achieving an effective balance among four performance metrics.Comparative analysis shows that the overall performance of the proposed algorithm outperforms several mainstream algorithms,and can effectively improve the efficiency and scientific rigor of air-defense firepower allocation decisions.Meanwhile,as the problem complexity increases,the proposed algorithm retains high optimization efficiency and acceptable computational load,demonstrating favorable scalability.

Key words： weapon-target assignment; multi-objective optimization; quantum particle swarm optimization; variable neighborhood search

Cite this article

ZHANG Teng , WANG Zheng , WANG Xuyang , WU Songsen , WEI Yali , WANG Xiaotian , NING Xin , CHEN Zhansheng . A Target Assignment Method Based on Variable Neighborhood Quantum Particle Swarm Optimization for Heterogeneous Anti-unmanned Equipment Swarms[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2026 , 46(1) : 61 -76 . DOI: 10.15892/j.cnki.djzdxb.2026.01.007

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