关键词: 在线订单拣选, 订单分批, 拣选路径, 聚类算法, 遗传算法

Abstract: In the person-to-goods order picking system, after the customer places the order, the picker shuttles the warehouse to pick it. This paper studies the online order batching optimization problem under the condition that the capacity of the warehouse’s picking equipment and the number of picking personnel are limited, so as to prevent premature order or delayed service to complete the picking task in the shortest time. This paper constructs an online order batch planning model considering the minimum picking path to minimize the average effective order service time, and proposes a rule-based heuristic algorithm to solve the model, which includes [k]-means clustering algorithm and genetic algorithm to process separately orders planning of batching and picking paths. Finally, a specific example is used for simulation calculation. The experimental results show that compared with the traditional fixed time window heuristic algorithm, the proposed rule-based heuristic algorithm can significantly improve the efficiency of picking.

Key words: online order picking, order batching, picking path, clustering algorithm, genetic algorithm