• Louis G. Birta
  • Gilbert Arbez
Part of the Simulation Foundations, Methods and Applications book series (SFMA)


Chapter 1 is the first of the two chapters of Part I of this book. The topics explored in these two initial chapters can be reasonably regarded as background material for the discussions in the remainder of the book. The discussion in this chapter examines such fundament notions as the nature of a model and typical reasons why a modelling and simulation study might be undertaken. A full-service gas station is used as a simple context for illustrating some of the issues that could arise in the formulation of a modelling and simulation project. It is acknowledged that modelling and simulation studies can fail and some common reasons for failure are identified. The contemporary version of the modelling and simulation paradigm is very much linked to the evolution of modern computing technology. The nature of this interrelationship is outlined in a brief review of the development of this increasingly pervasive problem-solving methodology.


Flight Simulator Simulation Project Elevator System Short Queue Payment Function 
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  1. 1.
    Bowden R (1998) The spectrum of simulation software. IEE Solut 30(May):44–54Google Scholar
  2. 2.
    Cohen J (ed) (2006) Endoscopy simulators for training and assessment skills. Gastrointest Endosc Clin North America 16(3):389–610. See also:
  3. 3.
    Rizzoli AE (2009) A collection of modelling and simulation resources on the internet. Available at∼andrea/sim/simtools.html
  4. 4.
    Mustafee N, Katsaliaki K, Fishwick P, Williams MD (2012) SCS: 60 years and counting! A time to reflect on the society’s scholarly contribution to M&S from the turn of the millennium. Simul: Trans Soc Model Simul Int 88:1047–1071CrossRefGoogle Scholar
  5. 5.
    Nance RE, Sargent RG (2002) Perspectives on the evolution of simulation. Oper Res 50:161–172MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Nance RE (1993) A history of discrete event simulation programming languages. ACM SIGPLAN Notices 28(3):149–175CrossRefGoogle Scholar
  7. 7.
    Nance RE (1995) Simulation programming languages: an abridged history. In: Proceedings of the 1995 winter simulation conference, Arlington VA, IEEE, pp 1307–1313Google Scholar
  8. 8.
    Ören TI, Zeigler BP (1979) Concepts for advanced simulation methodologies. Simulation 32:69–82CrossRefGoogle Scholar
  9. 9.
    Ören TI, Elzas MS, Smit I, Birta LG (2002) A code of professional ethics for simulationists. In: Proceedings of the 2002 summer computer simulation conference, Society for Computer Simulation International, San Diego, CA, pp 434–435Google Scholar
  10. 10.
    Nikoukaran J, Hlupic V, Paul RJ (1999) A hierarchical framework for evaluating simulation software. Simul Pract Theory 7:219–231CrossRefGoogle Scholar
  11. 11.
    Swain JJ (2005) Seventh biennial survey of discrete event simulation software tools. OR/MS Today 32(6):44–55Google Scholar
  12. 12.
    Wolffe G, Yurcik W, Osborne H, Holloday M (2002) Teaching computer organization/architecture with limited resources using simulators. In: Proceedings of the 33rd technical symposium on computer science education. ACM Press, New YorkGoogle Scholar
  13. 13.
    Yurcik W (2002) Computer architecture simulators are not as good as the real thing – they are better! ACM J Educ Resour Comput 1(4), (guest editorial, special issue on General Computer Architecture Simulators)Google Scholar
  14. 14.
    Zeigler BP, Praehofer H, Kim TG (2000) Theory of modeling and simulation: integrating discrete event and continuous complex dynamic systems, 2nd edn. Academic Press, San DiegoGoogle Scholar

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Louis G. Birta
    • 1
  • Gilbert Arbez
    • 1
  1. 1.School of Electrical Engineering and Computer ScienceUniversity of OttawaOttawaCanada

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