基于大邻域搜索算法的储位分配研究

Research on Storage Allocation Based on Large Neighborhood Search Algorithm

为了提升无人仓系统订单拣选效率,以同一货架上商品关联度之和最大为目标,构建了混合整数规划模型;设计了针对上述问题的大邻域搜索算法,在大邻域搜索算法中设计了多种破坏与修复算子。利用三种规模的算例对设计算子进行比较,结果证明随机移除—最大后悔插入组合算法相比其他组合算法在时间和性能上更加优越。

In order to improve the order picking efficiency of the unmanned warehouse system,a mixed integer programming model is constructed with the goal of maximizing the sum of the correlation degrees of goods on the same shelf.A large neighborhood search algorithm for the above problems is designed,in which a variety of damage and repair operators are designed.Using three scale examples to compare the design operators,the results show that the random removal-maximum regret insertion combinatorial algorithm proposed in the paper is superior in time and performance compared with other combinatorial algorithms.