基于改进元胞蚁群算法的铁路取送车问题研究

Research on the problem of placing-in and taking-out wagons based on improved cellular ant colony algorithm

为了有效并且快速地解决树枝型专用线取送车问题,文章提出了一种基于元胞自动机(cellular automata,CA)模型的改进蚁群算法,即改进元胞蚁群算法(improved cellular ant colony algorithm,ICACA)。通过对蚁群算法中的转移概率以及信息更新策略加以改进,同时将元胞的演化规则和蚁群的信息素更新规则结合,提高了蚁群的全局优化能力;为了防止陷入局部最优,算法中设计了交换策略。仿真结果表明,文中提出的ICACA能够有效提高取送车作业问题的效率。

In order to solve the problem of placing in and taking out wagons on branch shaped sidings quickly and effectively, this paper proposes an improved ant colony algorithm based on cellular automata（CA） model, namely the improved cellular ant colony algorithm（ICACA）. The global optimization ability of ant colony is improved by improving transition probability and strategy of updating pheromone of the algorithm, and combining the cellular evolution rules with the pheromone updating rule of ant colony. In the meantime, the exchange strategy is designed in the algorithm to avoid failing into local optimum. The simulation results show that the proposed ICACA can solve the problem of placing in and taking-out wagons effectively.