基于模糊机会约束双层规划的动态火力分配建模与实现

针对现有动态火力分配模型未考虑不确定因素及复杂约束的问题,引入不确定规划理论,建立了基于模糊机会约束双层规划的动态火力分配模型.首先,以最大化效费比和尽早拦截分别作为模型的上下层目标函数,并考虑复杂战场环境下的模型约束.在此基础上,构建了一种针对双层多约束动态火力分配问题的递阶结构粒子编码方案,并将带审敛因子的离散变邻域粒子群算法及带怀疑因子及斥力因子的粒子群算法有效结合,利用模糊模拟技术,提出一种分层递阶的混合模糊粒子群算法.仿真实例表明,该算法具有更强的全局寻优能力和更快的收敛速度,能够满足大规模动态火力分配问题对时效性的高要求.

Modeling and realization of dynamic firepower allocation problem based on fuzzy chance constrained bilevel programming

The dynamic firepower allocation (DFA) optimization model based on fuzzy chance constrained bilevel programming (FCCBLP) is presented on the basis of analyzing the deficiency of the existing DFA model. Firstly, employing the maximization cost-effectiveness ratio and earliest intercept time respectively as the upper and the lower objective function of the model, and considering the complex constraint condition so as to close to the battlefield environment. Secondly, particle coding scheme with hierarchical structure for multi-constrained bilevel DFA problem is constructed. On this basis, the hierarchical hybrid fuzzy particle swarm optimization (HHFPSO) algorithm is proposed with fuzzy simulation technique, which effectively combines two algorithms:the discrete variable neighborhood PSO algorithm with convergence criterions (DVNPSO-CC) and the PSO algorithm with doubt and repulsion factor (PSO-DR). Finally, computational results show the proposed algorithm has faster convergence speed and stronger global searching ability, which can satisfy the high requirements on the timeliness of the large-scale DFA problem.