This paper focuses on warehouse order picking optimization. It introduces a neural network-based metamodel trained on AnyLogic simulation data to predict the order fulfillment time in automated multi-level shuttle warehouses.
Explore how a training facility at Auburn University is teaching students and professionals lean manufacturing by assembling LEGO® cars. Through a multi-phase plan, the facility is evolving into a hub for digital manufacturing and Industry 4.0 technologies, with a focus on small and medium manufacturers (SMMs). The current phase involves creating an agent-based digital twin model to simulate and optimize assembly line processes.
This paper presents a tool for logistics optimization of Less-Than-Truckload terminals addressing rising service demands and shipment volumes. The tool enables efficient layout planning and resource allocation for small and medium-sized enterprises through automatic model generation and customizable simulation models.
A PortalLite system is a maritime logistics concept aimed at improving accessibility to remote areas, reducing environmental impact, and easing urban congestion through a network of small, distributed ports. In this study, the authors use both simulation and mathematical modeling to explore the feasibility and efficiency of this unique system.
This article explores the use of AnyLogic to optimize hydrogen refueling infrastructure for heavy-duty trucks in Bremen, Germany. It showcases possible advancements in renewable energy in transportation and hydrogen infrastructure optimization.
The paper discusses how process mining can be used to gain insights and automatically regulate processes in real time. It highlights the need for thorough testing to avoid side effects and proposes using discrete-event simulation in production and logistics to mitigate risks.
Creating discrete-event simulation models for adaptable material flow systems is challenging due to the need for various structural variants. This paper unveils an innovative method to automate this process, illustrated by a case study, which makes it easier and more efficient.
The research paper on e-commerce addresses urban logistics issues worsened by the COVID-19 pandemic. The scholars used system dynamics simulation modeling with the ε-constraint method to design a parcel locker delivery network and forecast demand. The model suggested the lockers’ locations for improved delivery results and helped to develop a strategy for minimizing environmental impact.
This research introduces a cloud-based hybrid simulation model that combines discrete-event simulation (DES) and agent-based modeling (ABM) to enhance Amazon warehouse yard operations, which are crucial for efficient logistics. By leveraging cloud technology for scalability and real-time data integration, the model dynamically simulates sequential processes and the interactions of autonomous agents, such as trucks and yard staff.