Cross-docking is a warehousing method that allows goods to move quickly from inbound suppliers directly to outbound customers, minimizing storage time. This study focuses on developing a real-time multi-agent truck scheduling model to optimize the process of cross-docking in warehouses, aiming for quick and efficient synchronization of incoming and outgoing freight.
Maritime traffic in winter in the Baltic Sea (particularly the northern part) is challenged by heavy ice formation. This work presented an integration of ice characteristics, operational-level details of ships, and system-level details such as traffic flows and icebreaker scheduling through a simulation framework.
The constant rise of e-commerce coupled with extremely fast deliveries is a significant contributor to saturate city centers’ mobility. To address this issue, the development of a convenient Automated Parcel Lockers (APLs) network improves last-mile distribution by reducing the number of transportation vehicles, the distances driven, and the delivery stops. An agent-based model was implemented in the current paper to forecast parcel demand placed on APLs based on socio-economic factors.
The bullwhip effect, a phenomenon of progressively larger distortion of demands across a supply chain, can cause chaos and disorder with amplified supply and demand misalignment. An agent-based simulation model was developed to evaluate how risk pooling and information sharing between distinct entities in a supply chain can reduce the bullwhip effects. In agent-based paradigm different components of a system were described as agents which interact with each other in an environment.
This study investigates a different source of uncertainty, which is the waiting time for the next vessel that is scheduled on a specific route, connecting two international ports. The aim of this research was to determine the booking size for vessels in oversea delivery to minimize transportation costs. The simulation model and all the respective processes included in the oversea supply chain were developed in AnyLogic with a discrete-event paradigm.
This paper considers a loading facility that uses Truck Appointment System (TAS) for slot management and faces incoming truck arrival uncertainty due to traffic congestion. The researchers developed an integer mathematical model to represent the adaptive behavior that determines the optimal reschedules by minimizing the average truck waiting time. The model was aimed to emulate the adaptive system. It was created in AnyLogic simulation software based on the conceptual model.
Commercial companies are looking at drones as a viable source of package transportation. Many supply chains have started to experiment with drone delivery systems and simulation modeling helps with such investigations a lot. The developers modeled the drone delivery problem with agent-based simulation and optimized the locations of drone depots and charging stations.
Co-design (concurrent engineering) is an important prerequisite for finding the best design solution for both future aircraft and the corresponding industrial systems. This paper discusses the use of simulation in the process of co-defining the optimal industrial system configuration for a future aircraft.
Based on an authentic model of system dynamics, the authors propose a new approach to simulation modeling of the dissemination of electric vehicles in a given region. The proposed system dynamics model made it possible to identify measures required to stimulate EV demand in a region with a low level of electric transport development.
This paper introduces a simulation study of interventions to ensure a stable supply of a generic medicine in Norway. A hybrid simulation modeling framework is proposed to evaluate the effect of alternative supply chain shortage interventions in response to various disruptions to support national decision making with respect to preparedness planning and emergency response.