基于模糊随机规划的反TBM目标分配优化模型

针对反导目标分配优化问题中存在的不确定性特征,引入模糊随机规划理论.首先建立了基于模糊随机规划的反战术弹道导弹(tactical ballistic missile,TBM)的目标分配优化模型.在此基础上,构建了一种针对多约束目标分配问题的粒子编码方案,并改进传统粒子群算法的位置和速度更新方式,提出了改进型离散粒子群(improve discrete particle swarm optimization,IDPSO)算法.最后,设计了模糊随机模拟技术和IDPSO算法相结合的混合智能求解算法.仿真实例表明,混合智能算法全局寻优能力强,优化效率高,满足反TBM目标分配优化对时效性的要求.

The model of anti-TBM target allocation optimization based on fuzzy random programming

For much uncertainty characteristic, the theory of fuzzy random programming is introduced into anti-tactical ballistic missile (TBM) target allocation optimization problem. Firstly, The model of anti-TBM target allocation optimization based on fuzzy random programming is constructed. Furthermore, the improved discrete particle swarm optimization (IDPSO) algorithm is proposed on the basis of the effective particle decoding scheme. Then, the hybrid intelligent algorithm is designed to solve the model, which integrates the technique of fuzzy random simulation and IDPSO algorithm. Finally, experimental results demonstrate the feasibility of hybrid intelligent algorithm for solving the proposed model.