IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v6y1959i1p92-110.html
   My bibliography  Save this article

Some Problems of Digital Systems Simulation

Author

Listed:
  • R. W. Conway

    (Department of Industrial and Engineering Administration, Cornell University)

  • B. M. Johnson

    (Department of Industrial and Engineering Administration, Cornell University)

  • W. L. Maxwell

    (Department of Industrial and Engineering Administration, Cornell University)

Abstract

Our objective is to discuss the technique of digital system simulation. This procedure has already achieved a considerable stature in industrial and research organizations and promises to attain even greater importance in the future. Yet, with few exceptions (5) 1 , the published literature in the area consists of introductory expositions (10) or of descriptions of the solution of a particular problem (7) where the technique itself is correctly relegated to secondary position. The only publication devoted entirely to the topic (12) is a compendium of papers of the latter type with little attempt to summarize or generalize. Simulations are, of course, as varied as the systems which they represent but they do have certain common characteristics and problems. An identification of these problems would at least allow the investigator to anticipate them and plan accordingly. This paper consists of three sections. The first is an attempt to describe characteristics common to many system simulations; the second is a discussion of some problems involved in the construction of a digital simulator; and the third concerns problems that arise in the use of such a simulator.

Suggested Citation

  • R. W. Conway & B. M. Johnson & W. L. Maxwell, 1959. "Some Problems of Digital Systems Simulation," Management Science, INFORMS, vol. 6(1), pages 92-110, October.
    • Handle: RePEc:inm:ormnsc:v:6:y:1959:i:1:p:92-110
    DOI: 10.1287/mnsc.6.1.92
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.6.1.92
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.6.1.92?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Song, Wheyming Tina, 1996. "On the estimation of optimal batch sizes in the analysis of simulation output," European Journal of Operational Research, Elsevier, vol. 88(2), pages 304-319, January.
    2. Peter Moran & Michele Simoni & Gianluca Vagnani, 2011. "Becoming the best: by beating or ignoring the best? Toward an expanded view of the role of managerial selection in complex and turbulent environments," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 15(3), pages 447-481, August.
    3. Enrico Cozzoni & Carmine Passavanti & Cristina Ponsiglione & Simonetta Primario & Pierluigi Rippa, 2021. "Interorganizational Collaboration in Innovation Networks: An Agent Based Model for Responsible Research and Innovation in Additive Manufacturing," Sustainability, MDPI, vol. 13(13), pages 1-17, July.
    4. Vagnani, Gianluca, 2009. "The Black-Scholes model as a determinant of the implied volatility smile: A simulation study," Journal of Economic Behavior & Organization, Elsevier, vol. 72(1), pages 103-118, October.
    5. Xuefei Lu & Alessandro Rudi & Emanuele Borgonovo & Lorenzo Rosasco, 2020. "Faster Kriging: Facing High-Dimensional Simulators," Operations Research, INFORMS, vol. 68(1), pages 233-249, January.
    6. Barry L. Nelson, 2004. "50th Anniversary Article: Stochastic Simulation Research in Management Science," Management Science, INFORMS, vol. 50(7), pages 855-868, July.
    7. Gianluca Vagnani, 2009. "The Black-Scholes model as a determinant of the implied volatility smile: A simulation study," Post-Print hal-00736952, HAL.
    8. Rand, William & Rust, Roland T., 2011. "Agent-based modeling in marketing: Guidelines for rigor," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 181-193.
    9. Wright, A. & Dent, J. Barry, 1969. "The Application Of Simulation Techniques To The Study Of Grazing Systems," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 13(2), pages 1-10, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:6:y:1959:i:1:p:92-110. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.