基于蚁群算法的LED分拣路径优化

LED Sorting Path Optimization Based on Ant Colony Optimization

提出基于蚁群算法对LED芯片分拣路径进行优化。对分拣工作芯片块间移动策略进行分析,降低盘片变形。在此基础上采用蚁群算法,建立分拣路径的全连接无向图并对分拣时间、分拣路径模型进行建模和优化。对蚂蚁数量、蚁群算法的时间复杂度、信息素挥发因子等参数进行优化。试验表明,该方法与传统方法相比能够缩短分拣时间,提高效率,为LED芯片分拣路径规划提供了一种有效的方法。

Ant colony optimization （ACO） is used to optimize LED sorting path. Block moving tactic of sorting are analyzed. The LED diaphragm＇s deformation is reduced. The fully connected undirected graph of sorting path is established and sorting time sequence and sorting path tactic are modeled and optimized by means of ACO. The number of ants, complexity of ant colony algorithm and factor of pheromone volatilizing are optimized. Experiments show that ACO is efficient in LED sorting, compared with the traditional one. An efficient method is offered for LED chip sorting path scheduling.