RAWSim-O: A Simulation Framework for Robotic Mobile Fulfillment Systems
This work addresses operational challenges in warehousing systems using robots, but it is incremental as it focuses on simulation development without major breakthroughs.
The paper tackles decision problems in Robotic Mobile Fulfillment Systems (RMFS), such as pod reallocation and selection, by developing a simulation framework called RAWSim-O and demonstrates its application with simple robot prototypes.
This paper deals with a new type of warehousing system, Robotic Mobile Fulfillment Systems (RMFS). In such systems, robots are sent to carry storage units, so-called "pods", from the inventory and bring them to human operators working at stations. At the stations, the items are picked according to customers' orders. There exist new decision problems in such systems, for example, the reallocation of pods after their visits at work stations or the selection of pods to fulfill orders. In order to analyze decision strategies for these decision problems and relations between them, we develop a simulation framework called "RAWSim-O" in this paper. Moreover, we show a real-world application of our simulation framework by integrating simple robot prototypes based on vacuum cleaning robots.