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The Simulation Modelling Process

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Simulation Strategies to Reduce Recidivism

Abstract

The purpose of this chapter is to provide a technical overview of simulation modelling. The author describes the appropriate uses of simulation techniques and how to approach simulation modelling beginning with the planning stages, through the various aspects of model building, validation and verification. The author focuses specifically on discrete-event simulation modelling techniques. It is a useful introduction and guide to simulation modelling for criminal justice researchers and practitioners.

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References

  • Ajzen, A. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.

    Article  Google Scholar 

  • Anderson, J. R., & Lebiere, C. (1998). The atomic components of thought. Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Bernhard, W. & Schilling, A. (1997). Simulation of group work processes in manufacturing. In Proceedings of the 1997 Winter Simulation Conference, SCS, Atlanta, GA, pp. 888–891.

    Google Scholar 

  • Brailsford, S., & Schmidt, B. (2003). Towards incorporating human behavior in models of health care systems: An approach using discrete-event simulation. European Journal of Operational Research, 150, 19–31.

    Article  Google Scholar 

  • Cavana, R. Y., Davies, P. K., Robson, R. M., & Wilson, K. J. (1999). Drivers of quality in health services: Different worldviews of clinicians and policy managers revealed. System Dynamics Review, 15(3), 331–340.

    Article  Google Scholar 

  • Elliman, T., Eatock, J., & Spencer, N. (2005). Modelling knowledge worker behavior in business process studies. Journal of Enterprise Information Management, 18(1), 79–94.

    Article  Google Scholar 

  • Forrester, J. (1961). Industrial dynamics. MA: Productivity Press, Cambridge.

    Google Scholar 

  • Greasley, A. (2004). Simulation modelling for business. Hants: Ashgate.

    Google Scholar 

  • Greasley, A., & Barlow, S. (1998). Using simulation modelling for BPR: Resource allocation in a police custody process. International Journal of Operations and Production Management, 18, 978–988.

    Article  Google Scholar 

  • Hanisch, A., Tolujew, J., Richter, K. & Schulze, T. (2003). Online simulation of pedestrian flow in public buildings. In Proceedings of the 2003 Winter Simulation Conference, SCS, New Orleans, LA, pp. 1635–1641.

    Google Scholar 

  • Hayes, C. C. (1999). Agents in a nutshell—A very brief introduction. IEEE Transactions on Knowledge and Data Engineering., 11(1), 127–132.

    Article  Google Scholar 

  • Johnson, R.T., Fowler, J.W. & Mackulak, G.T. (2005). A discrete event simulation model simplification technique. In Proceedings of the 2005 Winter Simulation Conference, SCS, Orlando, FL, pp. 2172–2176.

    Google Scholar 

  • Keller, J. (2002). Human performance modelling for discrete-event simulation: Workload. In Proceedings of the 2002 Winter Simulation Conference, San Diego, CA, pp. 157–162.

    Google Scholar 

  • Kelton, W. D., Sadowski, R. P., & Sturrock, D. T. (2007). Simulation with arena (4th ed.). New York, NY: McGraw-Hill.

    Google Scholar 

  • Lam, R. B. (2007). Agent-based simulations of service policy decisions. In Proceedings of the 2007 Winter Simulation Conference, SCS, Washington, DC, pp. 2241–2246.

    Google Scholar 

  • Law, A. M., & Kelton, W. D. (2000). Simulation modeling and analysis (3rd ed.). Singapore: McGraw-Hill.

    Google Scholar 

  • Macal, C.M. & North, M.J. (2006). Tutorial on agent-based modeling and simulation Part 2: How to model with agents. In Proceedings of the 2006 Winter Simulation Conference, SCS, Monterey, CA, pp. 73–83.

    Google Scholar 

  • Muller, D. J. (1996). Simulation: “What to do with the model afterward”. In J. M. Charnes, D. J. Morrice, D. T. Brunner, & J. J. Swain (Eds.), Proceedings of the 1996 Winter Simulation Conference. San Diego, CA: Society for Computer Simulation.

    Google Scholar 

  • Newell, A. (1990). Unified theories of cognition. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Pegden, C. D., Shannon, R. E., & Sadowski, R. P. (1995). Introduction to simulation using SIMAN (2nd ed.). Singapore: McGraw-Hill.

    Google Scholar 

  • Peppard, J., & Rowland, P. (1995). The essence of business process Re-engineering. Hemel Hempstead: Prentice Hall.

    Google Scholar 

  • Pew, R. W. (2008). More than 50 years of history and accomplishments in human performance model development. Human Factors, 50(3), 489–496.

    Article  Google Scholar 

  • Prichett, A. R., Lee, S. M., & Goldsman, D. (2001). Hybrid-system simulation for national airspace safety systems analysis. AIAA Journal of Aircraft, 38(5), 835–840.

    Article  Google Scholar 

  • Robinson, S., Edwards, J. S., & Yongfa, W. (2003). Linking the witness simulation software to an expert system to represent a decision-making process. Journal of Computing and Information Technology, 11(2), 123–133.

    Article  Google Scholar 

  • Robinson, S., Alifantis, T., Edwards, J. S., Ladbrook, J., & Waller, T. (2005). Knowledge based improvement: Simulation and artificial intelligence for identifying and improving human decision-making in an operations system. Journal of the Operational Research Society, 56(8), 912–921.

    Article  Google Scholar 

  • Schmidt, B. (2000). The modelling of human behavior. Erlangen: SCS.

    Google Scholar 

  • Schmidt, B. (2005). Human factors in complex systems: The modeling of human behavior. In Proceedings 19th European Conference of Modelling and Simulation, ECMS, Riga, Latvia.

    Google Scholar 

  • Shaw, A. P., & Pritchett, R. (2005). Agent-based modeling and simulation of socio-technical systems. In W. B. Rouse & K. R. Boff (Eds.), Organizational simulation. New York, NY: Wiley.

    Google Scholar 

  • Silverman, B. G., Cornwell, J., & O’Brien, K. (2003). Human performance simulation. In J. W. Ness, D. R. Rizer, & V. Tepe (Eds.), Metrics and methods in human performance research toward individual and small unit simulation. Washington DC: Human Systems Information Analysis Centre.

    Google Scholar 

  • Silverman, B. G. (1991). Expert critics: Operationalizing the judgement/decision making literature as a theory of “bugs” and repair strategies. Knowledge Acquisition, 3, 175–214.

    Article  Google Scholar 

  • Simulation Study Group. (1991). Simulation in U.K. manufacturing industry. In R. Horrocks (ed.). Coventry: The Management Consulting Group, University of Warwick Science Park.

    Google Scholar 

  • Stahl, I. (1995). New product development: When discrete simulation is preferable to system dynamics. In Proceedings of the 1995 EUROSIM conference. Amsterdam: Elsevier Science B.V.

    Google Scholar 

  • Sterman, J. D., Repenning, N. P., & Kofman, F. (1997). Unanticipated side effects of successful quality programs: Exploring a paradox of organizational improvement. Management Science, 43(4), 503–521.

    Article  Google Scholar 

  • Warren, R., Diller, D.E., Leung, A., & Ferguson, W. (2005), Simulating scenarios for research on culture & cognition using a commercial role-play game. In Proceedings of the 2005 Winter Simulation Conference, SCS, Orlando, FL, pp. 1109–1117.

    Google Scholar 

  • Welch, P. D. (1983). The statistical analysis of simulation results. In S. S. Lavenberg (Ed.), The computer performance modeling handbook (Vol. 9, No. 2, pp. 111–116). New York, NY: Academic.

    Google Scholar 

  • Wickens, C. D. (1984). Engineering psychology and human performance. New York, NY: Harper Collins.

    Google Scholar 

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Correspondence to Andrew Greasley Ph.D. .

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Greasley, A. (2013). The Simulation Modelling Process. In: Taxman, F., Pattavina, A. (eds) Simulation Strategies to Reduce Recidivism. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6188-3_3

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