摘要
为了提高基本蚁群算法的收敛性能和全局求解能力,对基本蚁群算法进行了改进,提出了一种改进的遗传混合蚁群算法。在每代进化中保留最优解和次优解的公共解集后引入遗传操作中的交叉算子进行运算,并采用自适应改变信息素挥发系数的方法,加快了算法收敛速度,提高了解的全局性。通过对TSP问题的仿真运算表明,改进的遗传混合蚁群算法在收敛速度和解的全局性上都有较大的改善。
To improve the efficiency of convergence and the global ability of basic ACA,a novel hybrid algorithm is proposed,which is an improved combination of GA and ACA.Cross operator is calculated after reserving the intersection of the best solution and the second best solution in every evolution,and the adaptive change pheromone volatile coefficient is affected.Convergence speed is accelerated and the global ability of the algorithm is improved.The simulations for TSP problem show that the improved algorithm has better convergence efficiency and global ability.
出处
《计算机时代》
2012年第11期31-32,36,共3页
Computer Era
基金
惠州市科技计划基金资助项目(2010B020008020)
关键词
蚁群算法
遗传算法
交叉算子
自适应
TSP
ant colony algorithm（ACA）
genetic algorithm（GA）
cross operator
the adaptive change
TSP
