Articles

Predictive Modeling in Healthcare: Assessing Interventions for Continuous Care of Cardiovascular Diseases after Natural Disasters


Predictive modeling in healthcare is crucial in assessing interventions for continuous care, especially for cardiovascular disease (CVD) patients affected by natural disasters. This study uses agent-based modeling in predictive simulation software to forecast health outcomes and plan effective public health interventions. By simulating hurricane events and patient responses, the research highlights the impact of medication adherence and disaster preparedness on reducing CVD mortality.

The Abade Artificial Archaeological Site Project


The paper explores the use of archaeology simulation, focusing on the Abade Artificial Archaeological Site Project. It highlights how technologies like laser scanning, 3D modeling, and agent-based simulations can be employed to reconstruct ancient settlements and provide new insights into historical research.

Analyzing Escalator Infrastructures: A Pilot Study in Santiago Metro


The behavior of passengers in urban railway stations (i.e., metro stations) is dependent on environmental, cultural, and temporal factors. In this research, escalator infrastructures were studied to better understand the relationship between different conditions and passenger behaviors through a method based on video cameras, passenger detection techniques, and a simulation framework.

A Multi-Agent-Based Real-Time Truck Scheduling Model for Cross-Docking Problems with Single Inbound and Outbound Doors


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.

Simulated-Based Analysis of Recovery Actions under Vendor-Managed Inventory Amid Black Swan Disruptions in the Semiconductor Industry: a Case Study from Infineon Technologies Ag


Through simulation modeling, this research highlighted the interactions of key system parameters in a disruption phase under different scenarios. A multi-period, multi-echelon serial supply chain was studied with agent-based and discrete-event simulation.

Agent-Based Learning Environment for Survey Research


Survey-based research methodology is commonly used in various disciplines, ranging from social sciences to healthcare. However, it is difficult to provide real-world experience of survey sampling methodologies to students and novice researchers. In this paper, the researchers proposed the development of a virtual learning environment based on agent-based modeling to help learn about different aspects and challenges of survey-based research.

System-Level Simulation of Maritime Traffic in Northern Baltic Sea


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.