ABSTRACT
Systems engineering for complex systems or system of systems cannot rely on a single method for modeling and analysis. However, established methods ranging from system dynamics (SD) to agent based simulation (ABS) can be applied to analyze specific domains. This paper introduces a spectrum of modeling & simulation (M&S) methods ranging from differential equations and highly aggregated models to high resolution models of individual behavior. Orchestration and choreography of all methods in this spectrum allow the seamless and continuous evaluation of complex systems and system of systems. A proposed classification is illustrated through two example problem domains: traffic and evacuation modeling.
- Smith EC Jr. (1962) Simulation in Systems Engineering. IBM Systems Journal, 1:1, 33 Google ScholarDigital Library
- Scholl HJ (2001) Agent-based and System Dynamics Modeling: A Call for Cross Study and Joint Research. Proceedings of the 34th Hawaii International Conference on System Sciences Google ScholarDigital Library
- Wakeland WW, Gallaher EJ, Macovsky LM, and Athena Aktipis C (2004) A Comparison of System Dynamics and Agent-Based Simulation Applied to the Study of Cellular Receptor Dynamics. Proceedings of the 37th Hawaii International Conference on System Sciences Google ScholarDigital Library
- Schieritz N (2004) Integrating System Dynamics and Agent-Based Modeling. Proceedings of the 20th System Dynamics Conference, Palermo, ItalyGoogle Scholar
- Law AM and Kelton WD (2000) Simulation Modeling and Analysis, 3rd Edition. McGraw Hill Google ScholarDigital Library
- Balci O (1998) Verification, Validation, and Testing, in Banks J (Ed), Handbook of Simulation, John Wiley & Sons, pp. 335--393 Google ScholarDigital Library
- Hillier FS and Lieberman GJ (2005) Introduction to Operations Research, 8th Edition, McGraw Hill Google ScholarDigital Library
- NATO Research & Technology Organization (2002) NATO's Code of Best Practice for Command and Control Assessment, revised Edition, CCRP PressGoogle Scholar
- Tolk A, Diallo SY, Turnitsa CD, and Winters LS (2006) Composable M&S Services for Net Centric Applications. Journal of Defense Modeling & Simulation 3 (1), pp. 27--44Google ScholarCross Ref
- Sargent RG (2001) Some Approaches and Paradigms for Verifying and Validating Simulation Models. Proceedings of the Winter Simulation Conference, IEEE Computer Press, pp. 106--114 Google ScholarDigital Library
- Sokolowski JA, Banks CM (Eds.) (2009) Principles of Modeling and Simulation: A Multidisciplinary Approach. WileyGoogle Scholar
- Page EH, Smith R (1998) Introduction to Military Training Simulation: A Guide for Discrete Event Simulationists. Proceedings of the Winter Simulation Conference, IEEE Computer Press, pp. 53--60 Google ScholarDigital Library
- Franck A, Zerbe V (2003) A Combined Continuous-Time/Discrete-Event Computation Model for Heterogeneous Simulation Systems. LNCS 2834, Springer, pp. 565--576Google Scholar
- Forrester J. (1961). Industrial Dynamics. Cambridge, MA: MIT PressGoogle Scholar
- Zeigler B, Praehofer H, Kim TG. (2000). Theory of Modeling and Simulation: Integrating Discrete Event and Continuous Complex Dynamic Systems, 2nd Edition. San Diego, CA: Academic Press Google ScholarDigital Library
- Yilmaz L, Ören T. (Eds.) (2009) Agent-directed Simulation and Systems Engineering, Wiley Google ScholarDigital Library
- Yilmaz L, Lim A, Bowen S, Ören T. (2007). Requirements and design principles for multisimulation with multiresolution, multistage multimodels. Proceedings of the Winter Simulation Conference, IEEE Computer Press, pp. 823--832 Google ScholarDigital Library
- "Analysis of Proposed Transportation Alternatives on the Hampton Roads Bridge Tunnel in 2030," Study results presented January 21, 2009 at the Virginia Modeling Analysis and Simulation Center, accessible via http://hrtpo.org/Presentations/2009/01_09/TransAlts-point_MPO&GA(JAN09)_novideo.pdf {last visited February 2010}Google Scholar
- Bazzan ALC, Wahle J, Klügl F. (1999). Agents in Traffic Modelling -- From Reactive to Social Behaviour. Proceedings KI-99: Advances in Artificial Intelligence, LNAI 1701, Springer, pp. 303?306 Google ScholarDigital Library
- Gwynne S, Galea ER, Owen M, Lawrence PJ, Filippidid L. (1999). A review of the methodologies used in the computer simulation of evacuation from the built environment. Building and Environment 34, pp. 741--749Google ScholarCross Ref
- MacGregor Smith J. (2009). Evacuation Networks. In Floudas CA, Pardalos PM (Eds.): Encyclopedia of Optimization, Second Edition. Springer, 940--950Google Scholar
- Santos G, Aguirre BE. (2005). Critical Review of Emergency Evacuation Simulation Models. Proceedings NIST Workshop on Building Occupant Movement during Fire Emergencies, NIST SP 1032, pp. 25--50Google Scholar
Recommendations
A modeling framework for the application of multi-paradigm simulation methods
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-...
Agent-directed simulation systems engineering
SCSC '07: Proceedings of the 2007 Summer Computer Simulation ConferenceThis article emphasizes the application of system engineering principles to the development of Modeling and Simulation (M&S) applications. Clear distinction between M&S for system engineering and system engineering (SE) for M&S is presented to clarify ...
The impact of spectrum policies on the secondary spectrum market
There has been a growing significance for Dynamic Spectrum Access (DSA) technology as a method to relieve the spectrum shortage problem and improve the efficiency of spectrum usage. For DSA technology to provide social and economic benefits, however, ...
Comments