Efficient order picking based on community detection

Order picking is the most labour-intensive and costly activity for almost every warehouse. In general, travel time of pickers during the order picking process is the dominant component of the total order picking time. This paper proposes an approach to decrease travel time by sharply cut down the step time in each picking operation. The reduction of step time is fulfilled by putting the goods nearby, which appear in a single order with higher probability. Social network and community detection are introduced into the discovering of the items which may be picked together in one picking operation. This method can bring higher efficiency and lower operation cost for distribution centers, and consequently for the whole supply chain.