城市作战的重要性日益凸显,城市作战路径规划也受到了更多的关注.如何在城市复杂的环境和众多危险区中寻找安全迅速的路径是非常重要的.为保障作战安全,提出了一种基于选拔科特鸟和路径缩减的不规则危险区路径规划算法.首先,结合城市危险区特征和受限情况以构建更符合真实战场的不规则危险区数学模型.其次,建立路径空间缩减模型对路径威胁度进行评估和量化,以剔除掉高威胁路径来降低作战风险.最后,基于选拔策略的科特鸟优化算法(COOT Bird Optimization Algorithm based on Selection Strategy,SS-COOT)结合优质个体以提高算法的寻优效率.经实验验证,该算法在结合不规则危险区的城市路径规划问题上具有搜索速度快、寻优效果好的特点.
Irregular Danger Zone Path Planning Based on SS-COOT and Path Space Reduction
The significance of urban warfare is increasingly prominent,prompting heightened attention to urban combat path planning.Finding secure and rapid paths amidst the complexity of urban environments and numerous danger zones is of paramount importance.To ensure combat safety and enhance operational efficiency,a path planning algorithm for irregular danger zones based on Selection Strategy COOT(SS-COOT)and path space reduction was proposed.Firstly,a mathematical model for irregular danger zones was constructed by incorporating the characteristics and limitations of urban danger zones,aligning with real battlefield scenarios.Secondly,a path space reduction model was developed to evaluate and quantify the threat level along various paths,eliminating high-threat paths to mitigate operational risks.Lastly,the SS-COOT optimization algorithm,integrating elite individuals,was employed to enhance the efficiency of the optimization process.Experimental validation demonstrates that the proposed algorithm exhibits rapid search speed and excellent optimization performance in the context of urban path planning with irregular danger zones.
万方数据
维普
