Abstract for: A Cross-Disciplinary Computational Framework for Hybrid Simulation and Modeling

Modeling and simulation (M&S) techniques are frequently used in Operations Research and Management Sciences to aid decision-making. With the growing complexity of systems to be modeled, an increasing number of studies now apply multiple M&S techniques or Hybrid Simulation comprising of a mix of simulation techniques. Hybrid Simulation, defined as a modeling approach that combines two or more of the following methods, discrete-event simulation, system dynamics, and agent-based simulation, has experienced near-exponential growth in popularity in the past two decades. A parallel but related theme of research is extending the Hybrid Simulation approach to include the development of Hybrid Models. Hybrid modeling combines research approaches, methods, techniques and tools from across disciplines to one or more stages of a simulation study. We conducted a structured and systematic literature review to study the development of the field of hybrid simulation and modeling. We aim to present the preliminary synthesis through conceptual representation and classification framework. Our classification framework and conceptual representation aims to support the advancement of hybrid modeling and contribute to the development of a set of guidelines to enable to report of cross-disciplinary research efforts in the M&S community, similar to the guidelines strengthening the reporting of empirical simulation studies.