IDEAS home Printed from https://ideas.repec.org/a/wly/navres/v62y2015i4p293-303.html
   My bibliography  Save this article

Changing the paradigm: Simulation, now a method of first resort

Author

Listed:
  • Thomas W. Lucas
  • W. David Kelton
  • Paul J. Sánchez
  • Susan M. Sanchez
  • Ben L. Anderson

Abstract

Decades ago, simulation was famously characterized as a “method of last resort,” to which analysts should turn only “when all else fails.” In those intervening decades, the technologies supporting simulation—computing hardware, simulation‐modeling paradigms, simulation software, design‐and‐analysis methods—have all advanced dramatically. We offer an updated view that simulation is now a very appealing option for modeling and analysis. When applied properly, simulation can provide fully as much insight, with as much precision as desired, as can exact analytical methods that are based on more restrictive assumptions. The fundamental advantage of simulation is that it can tolerate far less restrictive modeling assumptions, leading to an underlying model that is more reflective of reality and thus more valid, leading to better decisions. Published 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 293–303, 2015

Suggested Citation

  • Thomas W. Lucas & W. David Kelton & Paul J. Sánchez & Susan M. Sanchez & Ben L. Anderson, 2015. "Changing the paradigm: Simulation, now a method of first resort," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(4), pages 293-303, June.
    • Handle: RePEc:wly:navres:v:62:y:2015:i:4:p:293-303
    DOI: 10.1002/nav.21628
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nav.21628
    Download Restriction: no
    File URL: https://libkey.io/10.1002/nav.21628?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
    ---><---

    References listed on IDEAS

    as
    1. Pierre L'Ecuyer & Richard Simard & E. Jack Chen & W. David Kelton, 2002. "An Object-Oriented Random-Number Package with Many Long Streams and Substreams," Operations Research, INFORMS, vol. 50(6), pages 1073-1075, December.
    2. Jack P. C. Kleijnen & Susan M. Sanchez & Thomas W. Lucas & Thomas M. Cioppa, 2005. "State-of-the-Art Review: A User’s Guide to the Brave New World of Designing Simulation Experiments," INFORMS Journal on Computing, INFORMS, vol. 17(3), pages 263-289, August.
    3. Muer Yang & Michael J. Fry & W. David Kelton & Theodore T. Allen, 2014. "Improving Voting Systems through Service-Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 23(7), pages 1083-1097, July.
    4. Richard E. Nance & Robert G. Sargent, 2002. "Perspectives on the Evolution of Simulation," Operations Research, INFORMS, vol. 50(1), pages 161-172, February.
    5. Mahmut Parlar & Moosa Sharafali, 2008. "Dynamic Allocation of Airline Check-In Counters: A Queueing Optimization Approach," Management Science, INFORMS, vol. 54(8), pages 1410-1424, August.
    6. Muer Yang & Theodore Allen & Michael Fry & W. Kelton, 2013. "The call for equity: simulation optimization models to minimize the range of waiting times," IISE Transactions, Taylor & Francis Journals, vol. 45(7), pages 781-795.
    7. John Harling, 1958. "Simulation Techniques in Operations Research---A Review," Operations Research, INFORMS, vol. 6(3), pages 307-319, June.
    8. Thomas W. Lucas & John E. McGunnigle, 2003. "When is model complexity too much? Illustrating the benefits of simple models with Hughes' salvo equations," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(3), pages 197-217, April.
    9. Friedman, Milton & Schwartz, Anna J, 1991. "Alternative Approaches to Analyzing Economic Data," American Economic Review, American Economic Association, vol. 81(1), pages 39-49, March.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Manuel Chica & Joaquín Bautista & Jesica de Armas, 2019. "Benefits of robust multiobjective optimization for flexible automotive assembly line balancing," Flexible Services and Manufacturing Journal, Springer, vol. 31(1), pages 75-103, March.
    2. Parker, J.D. & Lucas, T.W. & Carlyle, W.M., 2024. "Sequentially extending space-filling experimental designs by optimally permuting and stacking columns of the design matrix," European Journal of Operational Research, Elsevier, vol. 319(2), pages 600-610.
    3. Anne E. Dohmen & Jason R. W. Merrick & Lance W. Saunders & Theodore P. Stank & Thomas J. Goldsby, 2023. "When preemptive risk mitigation is insufficient: The effectiveness of continuity and resilience techniques during COVID‐19," Production and Operations Management, Production and Operations Management Society, vol. 32(5), pages 1529-1549, May.
    4. Brian L. Morgan & Harrison C. Schramm & Jerry R. Smith, Jr. & Thomas W. Lucas & Mary L. McDonald & Paul J. Sánchez & Susan M. Sanchez & Stephen C. Upton, 2018. "Improving U.S. Navy Campaign Analyses with Big Data," Interfaces, INFORMS, vol. 48(2), pages 130-146, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yang, Muer & Wang, Xinfang (Jocelyn) & Xu, Nuo, 2015. "A robust voting machine allocation model to reduce extreme waiting," Omega, Elsevier, vol. 57(PB), pages 230-237.
    2. 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.
    3. Kumar, Sameer & Yang, Muer & Goldschmidt, Kyle H., 2018. "Will aging voting machines cause more voters to experience long waits?," International Journal of Production Economics, Elsevier, vol. 198(C), pages 1-10.
    4. Schmidt, Adam & Albert, Laura A., 2022. "Designing pandemic-resilient voting systems," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    5. Juan, Angel A. & Faulin, Javier & Grasman, Scott E. & Rabe, Markus & Figueira, Gonçalo, 2015. "A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems," Operations Research Perspectives, Elsevier, vol. 2(C), pages 62-72.
    6. George S. Tavlas, 2015. "In Old Chicago: Simons, Friedman, and the Development of Monetary‐Policy Rules," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(1), pages 99-121, February.
    7. Wen Shi & Xi Chen & Jennifer Shang, 2019. "An Efficient Morris Method-Based Framework for Simulation Factor Screening," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 745-770, October.
    8. P.A.V.B. Swamy & Jatinder S. Mehta & I-Lok Chang, 2017. "Endogeneity, Time-Varying Coefficients, and Incorrect vs. Correct Ways of Specifying the Error Terms of Econometric Models," Econometrics, MDPI, vol. 5(1), pages 1-17, February.
    9. Michael J. Armstrong, 2013. "The salvo combat model with area fire," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(8), pages 652-660, December.
    10. Pierre L'Ecuyer & Richard Simard, 2014. "On the Lattice Structure of a Special Class of Multiple Recursive Random Number Generators," INFORMS Journal on Computing, INFORMS, vol. 26(3), pages 449-460, August.
    11. Mehmet Tolga Cezik & Pierre L'Ecuyer, 2008. "Staffing Multiskill Call Centers via Linear Programming and Simulation," Management Science, INFORMS, vol. 54(2), pages 310-323, February.
    12. Dellino, Gabriella & Kleijnen, Jack P.C. & Meloni, Carlo, 2010. "Robust optimization in simulation: Taguchi and Response Surface Methodology," International Journal of Production Economics, Elsevier, vol. 125(1), pages 52-59, May.
    13. James Boughton, 1992. "International comparisons of money demand," Open Economies Review, Springer, vol. 3(3), pages 323-343, October.
    14. van Beers, Wim C.M. & Kleijnen, Jack P.C., 2008. "Customized sequential designs for random simulation experiments: Kriging metamodeling and bootstrapping," European Journal of Operational Research, Elsevier, vol. 186(3), pages 1099-1113, May.
    15. Yang, Yongjian & Yin, Yunqiang & Wang, Dujuan & Ignatius, Joshua & Cheng, T.C.E. & Dhamotharan, Lalitha, 2023. "Distributionally robust multi-period location-allocation with multiple resources and capacity levels in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1042-1062.
    16. Mirowski, Philip, 1995. "Three ways to think about testing in econometrics," Journal of Econometrics, Elsevier, vol. 67(1), pages 25-46, May.
    17. Scott E. Carrell & Bruce I. Sacerdote & James E. West, 2011. "From Natural Variation to Optimal Policy? The Lucas Critique Meets Peer Effects," NBER Working Papers 16865, National Bureau of Economic Research, Inc.
    18. Iago Medeiros & Lucas Pacheco & Denis Rosário & Cristiano Both & Jéferson Nobre & Eduardo Cerqueira & Lisandro Granville, 2021. "Quality of experience and quality of service‐aware handover for video transmission in heterogeneous networks," International Journal of Network Management, John Wiley & Sons, vol. 31(5), September.
    19. Lothian, James R. & Pownall, Rachel A.J. & Koedijk, Kees G., 2013. "I discovered the peso problem: Irving Fisher and the UIP puzzle," Journal of International Money and Finance, Elsevier, vol. 38(C), pages 5-17.
    20. Kampf, M. & Kochel, P., 2006. "Simulation-based sequencing and lot size optimisation for a production-and-inventory system with multiple items," International Journal of Production Economics, Elsevier, vol. 104(1), pages 191-200, November.

    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:wly:navres:v:62:y:2015:i:4:p:293-303. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1520-6750 .

    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.