Machine learning has become an important research area in many domains and real-world
applications. The prevailing assumption in traditional machine learning techniques, that …

Industry 4 (I4) was a revolutionary new stage for technological progress in manufacturing
which promised a new level of interconnectedness between a diverse range of …

In robotic mobile fulfillment systems, human pickers don't go to the inventory area to search
for and pick the ordered items. Instead, robots carry shelves (called “pods”) containing …

With the rapid development and implementation of ICT, academics and industrial
practitioners are widely applying robotic process automation (RPA) to enhance their …

The rapid development and implementation of the Internet of Things (IoT) and Cyber-
Physical Systems (CPS) in the engineering and manufacturing field have embraced a virtual …

Robotic mobile fulfillment systems is a large dynamic system where information such as
backlog, inventory, pod location, and robot state will change with time during its operation. In …

We study the order processing in KIVA robot-assisted warehouses, where racks are
delivered to multiple workstations by robots so that pickers at each workstation just focus on …

We propose a multi-agent simulation environment for logistics warehouses. Simulation is a
crucial part of designing industrial systems, such as logistics warehouses. A warehouse is a …

Robotic Mobile Fulfillment Systems (RMFS) are an example of warehouse automation.
Nonetheless, the complexity of RMFS is such that tackling the entire problem at once is …

Robotic mobile fulfillment systems (RMFSs) are a new type of warehousing system, which
has received more attention recently, due to increasing growth in the e-commerce sector …