research-article

Some Tactical Problems in Digital Simulation

Author: R. W. ConwayAuthors Info & Claims

Pages 47 - 61

https://doi.org/10.1287/mnsc.10.1.47

Published: 01 October 1963 Publication History

Abstract

This paper is concerned with the manner in which an investigation by simulated experimentation is conducted, after the model has been formulated and the computer program completed. It considers the problem of estimating the precision of the results obtained, and methods of improving the precision of results. Alternative procedures are discussed and recommendations are given.

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Vandin A(2024)Statistical Model Checking of Python Agent-Based Models: An Integration of MultiVeStA and MesaBridging the Gap Between AI and Reality10.1007/978-3-031-75434-0_26(398-419)Online publication date: 30-Oct-2024
https://dl.acm.org/doi/10.1007/978-3-031-75434-0_26
Verma AHanawal MRanzato MBeygelzimer ADauphin YLiang PVaughan J(2021)Stochastic multi-armed bandits with control variatesProceedings of the 35th International Conference on Neural Information Processing Systems10.5555/3540261.3542374(27592-27603)Online publication date: 6-Dec-2021
https://dl.acm.org/doi/10.5555/3540261.3542374
Lu XRudi ABorgonovo ERosasco L(2020)Faster KrigingOperations Research10.1287/opre.2019.186068:1(233-249)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1287/opre.2019.1860
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Some Tactical Problems in Digital Simulation

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Management Science Volume 10, Issue 1

October 1963

205 pages

ISSN:0025-1909

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INFORMS

Linthicum, MD, United States

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Published: 01 October 1963

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Vandin A(2024)Statistical Model Checking of Python Agent-Based Models: An Integration of MultiVeStA and MesaBridging the Gap Between AI and Reality10.1007/978-3-031-75434-0_26(398-419)Online publication date: 30-Oct-2024
https://dl.acm.org/doi/10.1007/978-3-031-75434-0_26
Verma AHanawal MRanzato MBeygelzimer ADauphin YLiang PVaughan J(2021)Stochastic multi-armed bandits with control variatesProceedings of the 35th International Conference on Neural Information Processing Systems10.5555/3540261.3542374(27592-27603)Online publication date: 6-Dec-2021
https://dl.acm.org/doi/10.5555/3540261.3542374
Lu XRudi ABorgonovo ERosasco L(2020)Faster KrigingOperations Research10.1287/opre.2019.186068:1(233-249)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1287/opre.2019.1860
Alexopoulos CGoldsman DMokashi AWilson JJohansson BJain S(2018)Sequential estimation of steady-state quantilesProceedings of the 2018 Winter Simulation Conference10.5555/3320516.3320736(1814-1825)Online publication date: 9-Dec-2018
https://dl.acm.org/doi/10.5555/3320516.3320736
Mustafee NBrailsford SDjanatliev AEldabi TKunc MTolk A(2017)Purpose and benefits of hybrid simulationProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242315(1-15)Online publication date: 3-Dec-2017
https://dl.acm.org/doi/10.5555/3242181.3242315
Balci OFujimoto RGoldsman DNance RZeigler B(2017)The state of innovation in modeling and simulationProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242244(1-16)Online publication date: 3-Dec-2017
https://dl.acm.org/doi/10.5555/3242181.3242244
Barton RNakayama MSchruben L(2017)History of improving statistical efficiencyProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242193(1-23)Online publication date: 3-Dec-2017
https://dl.acm.org/doi/10.5555/3242181.3242193
Fu MHenderson S(2017)History of seeking better solutions, aka simulation optimizationProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242192(1-27)Online publication date: 3-Dec-2017
https://dl.acm.org/doi/10.5555/3242181.3242192
Alexopoulos CKelton W(2017)A concise history of simulation output analysisProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242191(1-16)Online publication date: 3-Dec-2017
https://dl.acm.org/doi/10.5555/3242181.3242191
Flaxman ADeason ADolgert AMumford JSorensen REldrenkamp EVos TForeman KMokdad AWeaver M(2017)Untangling uncertainty with common random numbersProceedings of the Summer Simulation Multi-Conference10.5555/3140065.3140096(1-12)Online publication date: 9-Jul-2017
https://dl.acm.org/doi/10.5555/3140065.3140096
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Very efficient hybrid simulation methods for complex problems

Time-parallel multi-delay logic simulation

Inside discrete-event simulation software: how it works and why it matters

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