Pallets are returnable transport items and of great importance for supply chains. They ensure efficient storage, transport, and handling processes. The pallet cycle, however, is associated with a substantial effort. In addition to administrative costs, extra trips and detours must often be taken by forwarders to retrieve pallets or buy new pallets. In this paper, a fictitious cross-actor pallet exchange platform is analyzed by building a supply chain model.
Especially in complex manufacturing systems and uncertain conditions, sequencing operations in a machines’ queue can pose a difficult problem. To solve the problem, intelligent, adaptable, and autonomous systems have been developed using machine learning and simulation to sequence operations under uncertainty within large manufacturing systems.
This work aims at optimizing a public transportation network and its maintenance. In particular, it focuses on determining routes for replacement services and adjusting headways in case of scheduled shutdowns of subway lines. A simulation-based two-layer optimization approach is proposed to solve the problem.
Factors including hospital space layout, patient behavior, patient flow, and medical procedures interact and relate to each other, and ultimately affect efficiency and performance of healthcare facilities. And hospital layout planning can’t ignore such interdependencies.
This research integrates discrete event simulation (DES) and agent-based simulation (ABS) to help managers examine, plan, and compare different spatial design schemes through the modeling of patient behavior, patient flow, and the establishment of evaluation indexes.
This paper focuses on optimizing the production of a real-world pre-assembly facility in a high-volume and high-mix semiconductor wafer fab. In simulation software, the researchers built an in-depth, deterministic discrete-event model. With it, they tested release policies in two stages, using real production data and demands.
In Ireland, cheese is one of the most exported products. Due to Brexit, it will be most impacted by delays at ports caused by the potential reintroduction of customs or border controls. To predict forthcoming changes and analyze their impact on the cheese supply chain in Ireland, a simulation model was built. To develop the model, the research team used a combination of the agent-based and discrete event modeling approaches along with geographic information system (GIS) included in AnyLogic simulation software.
This paper presents a comprehensive production scheduling approach that combines optimization and simulation to cope with parameter uncertainty.
The approach allows for identifying and including demand fluctuations and scrap rates. Furthermore, the researchers adapt seven optimization algorithms for two-stage hybrid flow shops with unrelated machines, machine qualifications, and skipping stages with the objective to minimize the makespan.
The combination of methods is validated on a real production case of the automobile industry.
Overcrowding in the Emergency Department (ED) is one of the most important issues in healthcare systems. The lack of downstream beds can affect the quality of care for patients who need hospitalization after an ED visit.
This research proposes a generic simulation model as one of the ED overcrowding solutions to analyze patient pathways from the ED to hospital discharge. The model is adaptable for all pathologies and can include several hospitals within a healthcare network. To identify relevant pathways the research team conducts pathway analysis using Process Mining.
Diabetic retinopathy is a diabetes complication that affects eyes. It’s also the leading cause of blindness for working-age Americans. Early detection, timely treatment, and appropriate follow-up care reduce the risk of severe vision loss from DR by 95%. Unfortunately, less than 50% of people with diabetes follow the recommended eye care screening guidelines.
The research team developed a diabetic retinopathy care process model integrating the natural history of diabetic retinopathy with a patient’s interaction with the care system.
The negative effects of traffic, such as air quality problems and road congestion, put a strain on the
infrastructure of cities and high-populated areas. A potential measure to reduce these negative effects are grocery home deliveries (e-grocery), which can bundle driving activities and, hence, result in decreased traffic and related emission outputs.
This paper presents an agent-based simulation for logistics network analysis. The model built with a simulation tool assesses the impact of the e-grocery logistics network compared to the stationary one in terms of mileage and different emission outputs.