遗传-蚁群算法在目标分配问题中的应用研究

针对传统算法很难满足大型水面舰艇编队防空武器的武器目标分配(weapon target assignment,WTA)问题,提出一种将遗传算法融入蚁群算法的混合算法。分析了遗传算法和蚁群算法的优缺点、利用遗传算法快速全局随机搜索能力生成一组粗略解,用其作为蚁群算法的初始信息素,再利用蚁群算法的并行性、正反馈机制,最后求得最优解,并对遗传-蚁群算法与蚁群算法、遗传算法这3种方法进行仿真比较。分析结果证明:遗传-蚁群算法用更少的时间获得最优的火力分配方案,缩短了武器系统反应时间,在求解质量方面有较大优势。

Application of Genetic Ant-Colony Algorithm in Target Assignment Problem

As the traditional algorithm can＇t properly solve the antiair craft weapon target assignment problem of a grope of surface ships, a mixed algorithm which combines genetic algorithm with ant colony algorithm is presented. The advantage and disadvantage of genetic algorithm and ant colony algorithm are analyzed in detail. The optimal solution was obtained by using the parallelism and positive feedback mechanism. And the genetic-ant colony algorithm, genetic algorithm and ant colony algorithm were compared by simulating calculation. The result demonstrates that the genetic-ant colony algorithm is the most effective way to determine the optimal solution of fire assignment strategy, which reduces the weapon system response time, and has great advantage relating solution quality.