协同反潜指控决策建模及优化研究

Modeling and Optimization in Cooperative Anti-Submarine Command and Control

介绍了多目标优化模型。建立了协同反潜作战中目标威胁度和射击有利度模型,将遗传算法引入到指控决策优化过程中。设计了基于遗传算法的指控决策优化算法,并对算法作了适应度值乘幂变换和保存最优个体策略方面的改进。以编队协同防御为例,得到了未改进的遗传算法和改进的遗传算法的优化结果,并对两种方法的优化效果进行了比较,比较结果表明:无论是从算法的收敛速度还是寻优率方面,做过改进的算法都较未改进的算法优越。通过选择不同的初始种群进行多次试验的方法,验证了优化结果的正确性。

Multi-objective optimization model is introduced. Models of target-threaten and firefavorable in cooperative anti-submarine is proposed. Algorithm of genetic is applied in the control and decision making optimization method, with improvement in transformation of adaptive value power and the principle of best-individual to survive. Take cooperative defense of fleet as example, the optimized result of two methods has figured out and been analyzed, the result shows that improved method is better than the original one both in convergence speed of algorithm and optimized values. The results of repetitious experiments with different initialized values present the validity of optimization.