多目标激光反导决策的动态置换算法

Dynamical Permutation Algorithm for Multi-Object Laser Antimissile Decision

多目标激光反导决策优化是激光反导系统的关键技术,其本质上是一个动态最短路问题,但是目前对于寻求该问题的全局最优解存在很多困难,特别是当目标个数大于6时,很难获得全局最优解。针对多目标激光反导决策优化问题引入了一种动态置换算法,包括邻近置换和对称置换,其中邻近置换是在原有解的基础上进行微调,容易进入局部最优解,而对称置换则可以进行大范围的搜索,有利于跳出局部最优解,从而增加了获得全局最优解的概率。以8个目标为例进行了仿真,结果表明所提出的算法比遗传算法收敛速度快。

Multi-object laser antimissile decision optimization plays an important role in the laser antimissile system.It is a dynamical shortest path problem.But there are many barriers for finding the global optimal solution,especially when the number is greater than six.This paper introduces a dynamical permutation algorithm for this problem,which consists of two permutations called near permutation and symmetrical permutation respectively.The near permutation is the perturbation by the last solution and gets the local optimal solution easily.However,the symmetrical permutation can search in a larger region and jump out the local optimal solution.Therefore,this strategy increases the probability of obtaining the global optimal solution.Finally,taking eight targets as an example,the simulation results show that the convergence of the algorithm is faster than that of the genetic algorithm.