基于免疫记忆的蚁群算法的WTA问题求解  

Immune Memory-based Ant Colony Algorithm for Weapon-target Assignment Solution

作　　者：苏淼[1] 钱海[1] 王煦法[1] 

机构地区：[1]中国科学技术大学计算机科学技术系,合肥230027

出　　处：《计算机工程》2008年第4期215-217,共3页Computer Engineering

摘　　要：武器-目标分配(WTA)是影响武器系统作战有效性的重要因素之一。该文在蚁群算法中增加一个额外的记忆库,利用免疫记忆和克隆选择的思想和方法,提出了基于免疫记忆的蚁群算法(IMBACA),并用于求解武器-目标分配问题。分别用给定数据集和随机数据集的WTA问题进行实验,并与传统蚁群算法和蚁群算法的混合算法进行比较,结果显示IMBACA在解的质量和时间性能上均取得了较好的效果。Weapon-Target Assignment（WTA） is one of the key factors that affects the performance of weapon systems. By adding an extra immune memory library to the ant colony model, this paper proposes an Immune Memory-Based Ant Colony Algorithm（IMBACA） on the basis of the idea and method of immune memory and clone selection, to solve WTA problem. The algorithm is examined with the given and stochastic data set respectively, and compared with the traditional ant colony algorithm and GAACO. Experimental results indicate that the algorithm can evidently improve the performance of both solution quality and speed.

关 键 词：武器-目标分配 免疫记忆 蚁群算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]