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Forty years of discrete-event simulation—a personal reflection

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  • B W Hollocks

    (Bournemouth University Business School)

Abstract

Discrete-event simulation first emerged in the late 1950s and it has grown in popularity steadily to be now recognized as the most frequently used of the classical Operational Research techniques across a range of industries—manufacturing, travel, finance, health and beyond. I have been engaged with such simulation from 1964 up to the present day. This paper reviews the history and evolution of discrete-event simulation from his personal perspective, with a particular interest in software development up to 1992. Extrapolating from that history, the paper goes on to comment on the prospective continuing evolution of simulation and its software.

Suggested Citation

  • B W Hollocks, 2006. "Forty years of discrete-event simulation—a personal reflection," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(12), pages 1383-1399, December.
    • Handle: RePEc:pal:jorsoc:v:57:y:2006:i:12:d:10.1057_palgrave.jors.2602128
    DOI: 10.1057/palgrave.jors.2602128
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    References listed on IDEAS

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    1. David P. Christy & Hugh J. Watson, 1983. "The Application of Simulation: A Survey of Industry Practice," Interfaces, INFORMS, vol. 13(5), pages 47-52, October.
    2. R. W. Conway, 1963. "Some Tactical Problems in Digital Simulation," Management Science, INFORMS, vol. 10(1), pages 47-61, October.
    3. S Robinson, 2005. "Discrete-event simulation: from the pioneers to the present, what next?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 619-629, June.
    4. B Zarei, 2001. "Simulation for business process re-engineering: case study of a database management system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(12), pages 1327-1337, December.
    5. Jerry Banks & Eduardo Aviles & James R. McLaughlin & Robert C. Yuan, 1991. "The Simulator: New Member of the Simulation Family," Interfaces, INFORMS, vol. 21(2), pages 76-86, April.
    6. John Harling, 1958. "Simulation Techniques in Operations Research---A Review," Operations Research, INFORMS, vol. 6(3), pages 307-319, June.
    7. Richard E. Nance & Robert G. Sargent, 2002. "Perspectives on the Evolution of Simulation," Operations Research, INFORMS, vol. 50(1), pages 161-172, February.
    8. Hurrion, R. D., 1980. "An interactive visual simulation system for industrial management," European Journal of Operational Research, Elsevier, vol. 5(2), pages 86-93, August.
    9. R C H Cheng & J D Lamb, 2000. "Making efficient simulation experiments interactively with a desktop simulation package," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(4), pages 501-507, April.
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    Cited by:

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    2. J H Powell & N Mustafee, 2017. "Widening requirements capture with soft methods: an investigation of hybrid M&S studies in health care," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1211-1222, October.
    3. K Katsaliaki & N Mustafee & Y K Dwivedi & T Williams & J M Wilson, 2010. "A profile of OR research and practice published in the Journal of the Operational Research Society," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 82-94, January.
    4. S J E Taylor & T Eldabi & G Riley & R J Paul & M Pidd, 2009. "Simulation modelling is 50! Do we need a reality check?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 69-82, May.
    5. Carolyn M. Rutter & Alan M. Zaslavsky & Eric J. Feuer, 2011. "Dynamic Microsimulation Models for Health Outcomes," Medical Decision Making, , vol. 31(1), pages 10-18, January.
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    8. K Katsaliaki & N Mustafee, 2011. "Applications of simulation within the healthcare context," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(8), pages 1431-1451, August.

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