求解串并联系统备件配置问题的蚂蚁算法

Application of Ant Colony Algorithm in Series-parallel System

通过对串并联系统配置成本问题的分析提出了基于蚂蚁算法求解该问题的方法。蚂蚁算法作为一种生物进化算法但它与其他进化算法一样存在易陷入局部最小的缺点。在基本蚂蚁算法的基础上,通过修改它的信息素局域和全局更新规则,引入自适应的信息素挥发系数来提高收敛速度和算法的全局最优解搜索能力。实验结果表明,改进的蚂蚁算法具有很好的全局搜索能力,使全局收敛性及收敛速度两方面均得到提高。

This paper proposes an ant colony algorithm based new approach to analyze the cost of the seriesparallel system. The ant colony algorithm（ACA） is a widely accepted evolutionary algorithm. To avoid the limitation of ACA such as stagnation like other evolutionary algorithm, an improved ant colony algorithm is introduced to solve the cost problem by modifying pheromone and global updating strategy. A self adaptive pheromone evaporation rate is proposed, which can accelerate the convergence rate and improve the ability of searching an optimum solution. Experimental results showed that the proposed ant colony algorithm can provide quality global converging ability to enhance both the global convergency and convergence rate.