Decisions about modeling and simulation (M&S) of real-world systems need to be evaluated prior to implementation. Discrete Event, System Dynamics, and Agent Based are three different modeling and simulation approaches widely applied to enhance decision-making of M&S of these systems. Combining and/or integrating these methods can provide solutions to a plethora of systems’ problems. However, current solutions and frameworks do not provide guidance for selecting and deploying M&S models. Hence, the aim of this work is to present a generic modeling framework for combining and/or integrating Discrete Event, System Dynamics, and Agent Based simulation approaches. The framework is termed multi-paradigm modeling framework (MPMF). In this paper, we describe the research methodology that was followed for the development of MPMF, the different phases of MPMF, and the generic relationships of forming and deploying multi-paradigm simulation models. Then we evaluate the framework by using it for the implementation of a universal task analysis simulation model (UTASiMo). The MPMF provided guidance on what methods need to be incorporated into the UTASiMo models, what information is exchanged among those models, and how these models are connected and interact with each other.
Research on task analysis and human performance has focused on the development of adequate tools, models, and methods to understand, analyze, and improve the relationship between humans and systems. As technology continues to advance and to change the nature of human work, techniques of analysis are changing to meet the new needs. This work attempts to fill the gaps in the current task analysis tools and describes the architecture and development of a simulation model, named UTASiMo. UTASiMo is a simulation tool that aims to enhance task analysis by automatically generating a multi-method simulation model for well-defined tasks based on a spreadsheet template filled in by the user. The generated model analyzes and simulates tasks performed by individual simulated agents representing human operators while accounting for the estimation of an operator's utilization and error prediction. This work highlights the design, development, and evaluation of the hybrid architecture (discrete event and agent based) of UTASiMo. The development of the system dynamics model, which is responsible for the human error assessment, is a work in progress and is excluded from the present paper. A real-world case study has been adapted to evaluate the hybrid architecture of UTASiMo. The same case study was modeled using the Micro Saint simulation tool. The results produced by UTASiMo were compared with the real-world data as well as with the results produced by Micro Saint for validation purposes. The comparisons indicate the validity of the UTASiMo-generated model and also that the hybrid architecture produces more variability in the results than using only one method. The comparisons also show promise that the tool will reduce the time and effort of the task analysis simulation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.