This paper presents a framework that combines simulation with mathematical optimization to plan the supply of raw materials for producing specialty chemicals. A real-world use case was introduced to validate the developed framework, demonstrating the application of simulation in chemical industry logistics.
Efficient material replenishment in assembly plants can be optimized using autonomous mobile robots. This research analyzes the Tiger Motors assembly line at Auburn University, where a Stretch RE1 robot is integrated into the production process. A multimethod simulation model combining discrete-event and agent-based simulation modeling in AnyLogic evaluates different replenishment strategies. It identifies the most effective approach based on payload capacity, travel optimization, and real-time demand response.
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.
Efficient production scheduling is crucial for maximizing resource utilization in eco-industrial parks, where factories share energy and materials. However, balancing energy distribution and job scheduling is challenging due to fluctuating power availability, production constraints, and inter-factory dependencies. This study uses a constraint programming model in AnyLogic combining agent-based and discrete-event simulation modeling to optimize production in an industrial park.
The authors used AnyLogic multimethod simulation modeling and reinforcement learning to optimize resilient infrastructure restoration. This approach was applied to water distribution and mobility networks in Tampa, Florida, USA, enhancing decision-making, allowing for adaptive and efficient responses to disruptions, and improving resource allocation and operational resilience.
This article explores the integration of Vertical Lift Modules with shuttle-based storage and retrieval systems to enhance automated warehouse storage systems and improve order-picking efficiency. Using AnyLogic simulation, the research evaluates system performance through discrete-event and agent-based simulation modeling.
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 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.
Hybrid Simulation modeling has been grabbing researchers’ attention lately. This article reports on a preliminary review of the literature and investigates the prevalence and utilization of Hybrid Simulation in healthcare. Findings show that combining Discrete-Event Simulation and System Dynamics is the most common approach to developing HS models in healthcare. However, the popularity of combining Agent-Based Simulation with others is on the rise.