基于蚁群算法的智能生产物流体系构建研究

Research on Intelligent Production Logistics System Construction Based on Ant Colony Algorithm

随着可利用土地资源的日益稀缺,物流企业为降低成本,提高存储密度,对智能生产物流仓储的要求愈加迫切。提高存储密度的一个重要途径是尽量减少巷道,与单倍货架相比,智能仓储货架节约了巷道空间,从而实现了智能生产物流体系的仓储。在考虑配货机的运行时间和配货机在货位的停留时间的基础上,建立配货机执行交叉存取指令的智能货位优化模型。为减少翻箱操作次数,根据智能生产物流的仓储结构特征提出蚁群算法对模型进行求解。仿真实验显示:当存储密度为85%时,与随机存储算法对比,蚁群算法提高了27.39%。

It is more urgent for logistics enterprises to reduce the cost and improve the storage density with the scarcity of available land resources. An important way to improve the storage density is to minimize the roadway. Compared with the single shelf,the intelligent storage shelf saves the roadway space,thus realizing the storage of the intelligent production logistics system. In considering picking machine running time and picking machine,the residence time of the location on the establishment of intelligent space optimization model is put forward to perform cross access instruction picking machine. In order to reduce the number of turns,according to the storage structure characteristics of intelligent production logistics,ant colony algorithm is put forward to solve the model. Simulation experiments show that when the storage density is 85%,compared with the random storage algorithm,the ant colony algorithm improves by 27.39%.