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.
@article{arxiv.1710.04726,
title = {RAWSim-O: A Simulation Framework for Robotic Mobile Fulfillment Systems},
author = {Marius Merschformann and Lin Xie and Hanyi Li},
journal= {arXiv preprint arXiv:1710.04726},
year = {2021}
}