학술 기사

Developing an ED Overcrowding Solution to Improve the Quality of Care


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.

Using Diabetic Retinopathy Care Process Model to Evaluate Interventions


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.

Logistics Network Analysis Model of E-Grocery Built with a Simulation Tool


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.

Simulation as One of Logistics Optimization Techniques Helps Improve E-Grocery Delivery


E-commerce has increased tremendously in recent decades because of improvements in information and telecommunications technology along with changes in social lifestyles. More recently, e-grocery (groceries purchased online) including fresh vegetables and fruit, is gaining importance as the most-efficient delivery system in terms of cost and time.

This paper evaluates the effect of cooperation-based logistics policies, including horizontal cooperation, on service quality among different supermarkets in Pamplona, Spain. For that, the research team applies simulation modeling as a logistics optimization technique.

Patient Flow Management Policy Evaluation with Simulation Software


Healthcare is facing great challenges to make processes more efficient and meanwhile provide better service to patients. Management of the intensive care unit (ICU), which is one of the most critical departments in terms of patient status and patient flow, also tries to provide better service and reduce the mortality rate.

During COVID-19, effective and efficient management is of utmost importance. A patient flow model developed in AnyLogic simulation software allows a comprehensive evaluation of eleven different management policies for controlling ICU admissions when facing capacity shortages.

Risk-Adjusted Healthcare Staffing Policy During the Pandemic – Modeled with Simulation Software


During the pandemic specialty physicians are working as frontline workers due to hospital overcrowding and a lack of providers. This places them as a high-risk target of the epidemic. Within these specialties, anesthesiologists are one of the most vulnerable groups as they come in close contact with the patient's airway.

An agent-based simulation model was developed using AnyLogic software to test various staffing policies within the anesthesiology department of the largest healthcare provider in Upstate South Carolina.

Crane Scheduling at Steel Manufacturing Plant Using Simulation Software and AI


The overhead crane scheduling problem has been of interest to many researchers. While most approaches are optimization-based or use a combination of simulation and optimization, this research suggests a combination of dynamic simulation and reinforcement learning-based AI as a solution.

The goal of this steel plant simulation project was to minimize the crane waiting time at the LD converters by creating a better crane schedule.

Simulating an Automated Breakpack System to Improve Warehouse Efficiency and Operations


This case study focuses on the simulation of a soon-to-be-implemented automation system within a Walmart Canada warehouse. This new system's aim is more efficient warehouse operations. Many stock-keeping units (SKUs) cannot be sent to retail stores in full case quantities. They are slow movers and would require individual stores to carry excessive inventory.

Breakpack is the process of breaking cases down to individual eaches (pieces) and combining them into mixed SKU cartons. Automating breakpack offers significant labor and quality savings, that are important to ensure efficient warehouse operations, but also a high degree of complexity.