2023 Vol.6 Oct.N05

• Title: Research on ship-to-air missile fire distribution method based on improved genetic algorithm
• Name: Yuliang Sun
• Company: Dalian Naval Academy,DaLian,116018 China
• Abstract:

  The current conventional ship-to-air missile fire allocation methods mainly combine with dynamic planning algorithms to construct a target allocation model, which results in poor allocation due to the lack of determination of the timing of fire channel allocation. In this regard, an improved genetic algorithm-based ship-to-air missile fire allocation method is proposed. Combined with the fire allocation area, the fire threat level is ranked to determine the best allocation timing. The cross-regulation method and the variation probability of the traditional genetic algorithm are adjusted to construct a multi-target fire allocation function and solve it. In the experiments, the designed fire allocation algorithm is tested for the allocation performance. The final results can prove that the enemy threat degree is solved to a high degree when the proposed method is used for missile fire allocation, and it has a more desirable fire allocation performance.

  
  

• Keyword: genetic algorithm; ship-to-air missile; fire distribution method; multi-objective function;
• DOI: 10.12250/jpciams2023090711
• Citation form: Yuliang Sun.Research on ship-to-air missile fire distribution method based on improved genetic algorithm [J]. Computer Informatization and Mechanical System,2023,Vol.6,pp.49-54

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