A polling-based dynamic order picking system for online retailers

A review on stochastic models and analysis of warehouse operations

“…Bozer and Park [29] have studied single-device, polling-based material handling systems. Gong and De Koster [1] apply stochastic polling models to a warehouse dynamic order-picking system for an online retailer.…”

“…For instance, for warehouses of online retailers, the order size is relatively small and the total number of orders is relatively large, and the Poisson process can be used to approximate the order arrival process (see, e.g. Gong and De Koster [1]). However, the typical Poisson model cannot always accurately describe arrival processes in some application settings.…”

“…Queueing networks have been applied in warehouse research to some extent (e.g., Gong and De Koster [1], Meng and Heragu [1,65]). However, more general stochastic networks, one of the main recent exploration directions in stochastic research [64], have appeared to be promising in the operations and manufacturing areas, and can be explored further in warehousing.…”

Sorting System Study Based on the Stochastic and Exhaustive Parallel Limited-1 Polling Control Theory

“…With the application in wireless link and optimization of distributed garbage sorting system, it verified the optimized path mixed polling system configuration; Chernova et al [8] proposed a single server polling system with two queues, its stability region depending on the distribution of service time adaptive service strategy and a certain moment under the primitive index. Gong and Koster [9] used the stochastic polling theory, to research the problems of e-commerce dynamic Picking System modeling and solve the dynamic Picking manual picking system latency. Dongfeng Zhao et al [10,11] took advantages of probability generating function, constructed and analyzed the multi-level threshold polling system under the MAC discrete-time control protocol model, and explored the polling system of secondary site threshold services priority queues.…”

Dynamic warehouse optimization using predictive analytics.

“…Order tardiness and overtime costs of the pickers are minimized in their model. Gong and De Koster (2008) develop a dynamic order picking system, in which orders arrive in real-time and the picking information is dynamically changed during the picking operation. Therefore, the pick locations are not fixed in a picking cycle and the response time is reduced.…”