학술 기사

A Cloud-Based Hybrid Simulation Model for Amazon Warehouse Yard Operations Optimization


This research introduces a cloud-based hybrid simulation model that combines discrete-event simulation (DES) and agent-based modeling (ABM) to enhance Amazon warehouse yard operations, which are crucial for efficient logistics. By leveraging cloud technology for scalability and real-time data integration, the model dynamically simulates sequential processes and the interactions of autonomous agents, such as trucks and yard staff.

A Simulation Approach for COVID-19 Pandemic Assessment Based on Vaccine Logistics, SARS-CoV-2 Variants, and Spread Rate


Despite advances in clinical care for the coronavirus (COVID-19) pandemic, population-wide interventions were vital to effectively manage the pandemic due to its rapid spread and the emergence of different variants. One of the most important interventions to control the spread of the disease is vaccination. In this study, an extended Susceptible-Infected Healed (SIR) model based on system dynamics was designed, considering the factors affecting the rate of spread of the COVID-19 pandemic.

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.

Energy-Efficient Semiconductor Manufacturing: Establishing an Ecological Operating Curve


The semiconductor industry is facing pressure to reduce its extensive energy consumption, which requires transparency on the relationship between energy efficiency and original planning objectives. This paper aims to develop an extension to the existing Operating Curve concept by investigating the effect of utilization on energy efficiency. It uses the results of discrete-event simulation on a fab level to verify the novel concept.

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.

Data-Driven Simulation for Production Balancing and Optimization: a Case Study in the Fashion Luxury Industry


As widely reported in the literature, the leather luxury accessories industry is characterized by a highly fragmented supply chain. Frequent changes in the production mix had to be managed, often requiring the re-optimization or even re-design of production flows. The objective of this paper was to propose a data-driven simulation model for production balancing and optimization in this sector.

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.