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.
Active shooting events are, unfortunately, a common situation. To help civilians, first responders, and governments better understand how to deal with these, a model was developed to simulate such incidents. In addition, the Purdue Institute of Homeland Security built a library to make future models simpler to develop.
The aircraft turnaround process consists of "ground handling operations" that are required to set an aircraft ready for its subsequent departure. This work focuses on enhancing the planning and real-time allocation of apron operations that are used to turn around an aircraft between two consecutive flights.
Order picking is a labor-intensive operation and contributes significantly to overall operational costs in a warehouse. This research develops a simulation model to evaluate the performance of order picking with varying numbers of autonomous mobile robots (AMRs) and pickers, considering both traditional and cross-aisled warehouse layouts.
In this paper, researchers introduce two case studies that show how simulation and optimization help in overcoming many of the challenges associated with data science techniques. The methodology is easily extended to a wide range of industries and use cases and enables an organization to improve its decision-making and generate business value.
Simulation is one of the most used approaches to analyze semiconductor manufacturing systems. However, most simulation models are designed for single-use applications and study a limited set of problems that are not reusable afterwards. This paper proposes a generic, data-driven simulation model to evaluate and analyze a wide range of problems arising in modern semiconductor manufacturing systems.
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.