Hybrid conceptual modeling for simulation: An ontology approach during Covid-19
Document Type
Conference Item
Publication Date
1-1-2021
Abstract
The recent outbreak of Covid-19 caused by SARS-CoV-2 infection that started in Wuhan, China, has quickly spread worldwide. Due to the aggressive number of cases, the entire healthcare system has to respond and make decisions promptly to ensure it does not fail. Researchers have investigated the integration between ontology, algorithms and process modeling to facilitate simulation modeling in emergency departments and have produced a Minimal-Viable Simulation Ontology (MVSimO). However, the 'minimalism' of the ontology has yet to be explored to cover pandemic settings. Responding to this, modelers must redesign services that are Covid-19 safe and better reflect changing realities. This study proposes a novel method that conceptualizes processes within the domain from a Discrete-Event Simulation (DES) perspective and utilizes prediction data from an Agent-Based Simulation (ABS) model to improve the accuracy of existing models. This hybrid approach can be helpful to support local decision making around resources allocation. © 2021 IEEE.
Keywords
Decision making, Discrete event simulation, SARS, Algorithm model, Conceptual model, Emergency departments, Healthcare systems, Modeling for simulations, Novel methods, Ontology model, Ontology's, Process-models, Simulation-modelling, Ontology
Divisions
fsktm
Funders
None
Publication Title
Proceedings - Winter Simulation Conference
Volume
2021-D
Event Title
2021 Winter Simulation Conference, WSC 2021
Event Location
Phoenix
Event Dates
12-15 December 2021
Event Type
conference