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Key research themes
1. How can Discrete Event Simulation (DES) be extended and integrated with emerging data and computational technologies to enhance its modeling and decision support capabilities?
This research theme focuses on the augmentation of DES methodologies through the incorporation of big data analytics, cloud computing, open-source platforms, and modular distributed simulation frameworks. It addresses challenges related to scalability, flexibility, and accessibility of simulation models, aiming to empower both practitioners and researchers with enhanced modeling tools that can handle complex, data-intensive systems and leverage modern computational infra-structure.
Key finding: This paper presents a comprehensive literature review showing how big data analytics (including data mining, machine learning, and process mining) can be integrated at various stages of the discrete-event simulation... Read more
Key finding: The DREAM project introduces an open-source, cloud-enabled DES platform consisting of a simulation engine (ManPy), a knowledge extraction module, and a customizable web GUI. This modular architecture addresses the limitations... Read more
Key finding: The paper proposes CS-DEVS, a distributed, client-server DES framework with centralized event scheduling and modular components distributed over different nodes. This architecture decouples simulation modules and centralizes... Read more
Key finding: This article reports multi-year experiences implementing cloud-based frameworks to speed up discrete event simulation experiments by dynamically allocating distributed computing resources. It discusses applications of cloud... Read more
Key finding: JAPROSIM presents an open-source, Java-based discrete-event simulation library adopting the process-interaction worldview with an object-oriented design. The library supports easy and modular DES model construction by... Read more
2. What methodologies and conceptual translations enable large-scale agent-based models (ABM) to be executed efficiently using discrete event simulation frameworks?
This theme investigates the formal relationships and practical methods to map agent-based simulation models onto discrete event simulation engines. Addressing scalability bottlenecks in ABM execution, it examines how discrete event mechanisms can faithfully reproduce agent-based behaviors without requiring modelers to alter their original modeling paradigm. This research seeks to enhance computational performance and leverage well-established DES simulation engines for social, behavioral, or complex adaptive systems modeled via agents.
Key finding: The paper demonstrates mathematically that any agent-based model conforming to a given specification can be automatically and transparently translated into an equivalent discrete-event simulation model. This translation... Read more
Key finding: This work proposes a framework embedding multi-agent systems within the discrete event simulation paradigm tailored for social simulations. It defines the minimal DES components necessary to model social behaviors (states,... Read more
3. How are discrete event simulation models applied and adapted to improve healthcare system operations, especially emergency department management and policy development?
This research theme explores the design, validation, and use of DES models tailored to healthcare settings. It emphasizes participatory modeling approaches involving stakeholders, modeling patient flows under various conditions (including peak arrivals and disasters), and integrating DES to inform health policy. These studies address challenges in healthcare operational efficiency, resource allocation, and decision support to mitigate overcrowding and improve service delivery within emergency departments.
Key finding: The paper presents a four-stage participatory modeling framework that actively engages stakeholders in developing DES models of ED patient flows to identify wait time reduction strategies. Employing a multi-criteria... Read more
Key finding: Using a detailed ARENA-based DES model of a medium-sized Italian ED, this case study quantifies operational impacts from various patient surge patterns, including earthquake-induced peaks. By simulating multiple scenarios,... Read more
Key finding: This systematic review over recent years classifies and analyzes 311 DES studies in healthcare, identifying trends, focus areas, and application scales. It confirms DES’s suitability for modeling complex, stochastic... Read more