【摘要】 为了提高基本蚁群算法的全局求解能力,对基本蚁群算法进行了改进,提出了一种通过自适性改变启发式因子α和β期望启发式因子的蚁群算法。当连续几代进化后的最优解没有明显变化时,改进后的算法通过对启发式因子α和期望启发式因子的β自适应调整来提高最优解的求解质量。通过对TSP问题的仿真表明,改进后的蚁群算法在求解最优解和收敛性能方面比起基本蚁群算法存在优势。更多还原

【Abstract】 In order to improve the global ability of basic ACA(ant colony algorithm),a novel ACA algorithm which is an improved al-gorithm based on adaptively adjusting parameter α,β is proposed.When best solution has not changed after several generations,the novel ACA algorithm adaptively adjusts the parameter α,β to improve the global ability of the solution.The simulations for TSP problem show that the improved ACA algorithm can find better best solution and have better convergence than basic ACA.更多还原