一种改进的动态自适应最大-最小蚁群算法

An Improved MMAS with Dynamic Adaptive Property

最大—最小蚂蚁系统(MMAS)具有较强的全局最优解搜索能力,能够有效避免早熟收敛,但收敛速度较慢。针对MMAS的不足,改进其信息素更新方式,提出一种新的动态自适应调整信息素的策略。对TSP问题的仿真实验结果表明,改进后的算法加快了收敛速度,提高了全局搜索能力。

Max-min ant system （MMAS） has great ability of searching the whole best solution and availability of avoiding premature convergence, but at the same time there is defect of slow speed of convergence. In order to overcome the shortcoming of basic MMAS, it is improved in a way of updating pheromone and a new dynamic adaptive strategy of adjusting pheromone is adopted in this algorithm. Experimental results for solving TSP problems indicate that the improved algorithm increases the speed of convergence and enhances the ability of searching the whole best solution.