舰艇编队防空多平台多类型武器火力分配优化  

Optimization of Weapon Target Assignment with Multi-Launcher and Multi-Weapon for Naval Ship Formation

作　　者：王少蕾[1] 陈维义[1] 周菲[2] 

机构地区：[1]海军工程大学 [2]中国人民解放军91872部队

出　　处：《计算机仿真》2014年第1期18-21,30,共5页Computer Simulation

摘　　要：为了解决舰艇编队所面临的多批次、多种类目标饱和攻击的火力分配问题,提高突防能力,通过建立编队防空多平台多防空武器的火力分配模型,采用模拟退火策略的自适应遗传算法进行求解与仿真。采用特殊的染色体编码方式使其满足约束条件;利用混沌序列初始化种群,加强种群的多样性;充分利用遗传算法工具箱,自适应调节算法的交叉与变异概率,优化参数,改善算法的收敛性;模拟退火策略增强了算法的局部搜索能力。通过计算机仿真进行求解,优化了火力分配方案,说明改进方法在优化性能上有较大改进,能避免陷入局部最优。仿真验证了模型的可行性和算法的有效性,可为解决火力分配问题提供有效解决方案,为编队防空火力分配提供参考。For the purpose of solving the weapon-target assignment problem which naval warship formation is con- fronted with saturated attacks of multi-groups and multi-types targets, a warship formation antiaircraft weapon-target assignment model was established in allusion to the operation task requirements. An adaptive genetic algorithm with simulated annealing strategy for solving weapon-target assignment problems was proposed. By optimizing parameters of the algorithm, the constringency characteristic of solving such problem was improved. Aimed to the special require- ments of the model solving, a special chromosome coding data structure that can effectively express the warship forma- tion antiaircraft combat effectiveness was put forward. Chaotic sequence generated by logic self-mapping was used to initiate population to enhance the diversity of search strategy. The genetic algorithm toolbox was fully used, and the crossover and mutation operators were given to produce a higher effective weapon-target assignment result. Simulation results show that the method can provide effective solutions for weapon-target assignment problems, and the proposed algorithm has better performance than other proposed evolutionary algorithms. This method can provide support for formations＇ air-defense warfare operations.

关 键 词：防空作战 武器目标分配 自适应遗传算法 模拟退火 混沌映射 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]