基于移动机器人的订单拣选系统货位优化模型和算法研究
The Slotting Optimization Model and Algorithm in Robotic Mobile Fulfillment Systems
为了提高基于移动机器人的订单拣选系 统的拣选效率, 文章提出了基于货品相关性和货架中货品总出库频次的货位优化方法. 将货位优化分为货品存放到货架及货架布局到仓库中现有位置两个阶段, 为避免拥堵采用分散存储策略建立了最小化货架搬运次数以及最小化机器人总拣选路程的数学模型, 并设计两阶段启发式算法求解. 结合A网上药店的历史订单数据进行了仿真实验, 实验结果表明, 文章提出的货位优化方法有效提高了订单拣选效率.
In order to improve the efficiency of order picking in robotic mobile fulfillment system, a slotting optimization method which takes into account the the correlation of goods and the total frequency out of warehouse of goods on the shelf is proposed. The problem of slotting optimization is divided into two stages: Deciding which goods to put on which shelf and which shelf to put in which position in the warehouse. In order to avoid congestion, a decentralized storage strategy is adopted. Two mathematical models are established to minimize the total number of shelves movings and the total picking distance of robots, and a two-stage heuristic algorithm is designed to solve the models. Finally, the simulation experiment is carried out based on the historical order data of an online pharmacy. The experimental results show that the slotting optimization method proposed effectively improves the efficiency of order picking.
移动机器人拣选系统 / 货到人拣选模式 / 货位优化 / 两阶段启发式算法. {{custom_keyword}} /
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