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Simulation modeling for analysis

Schruben, Lee·2010·ACM Transactions on Modeling and Computer Simulation

Abstract

This article explores possibilities for designing and executing simulation models with specific analysis goals in mind, and shows that a tight coupling of the modeling and analysis phases in a simulation project can lead to dramatic improvements in the study results. Suggestions are made for how simulation analysis, considered in the explicit context of discrete-event simulation models, can create new opportunities for meaningful research and more efficient modeling. Modeling decisions can play a significant role in the performance of analytical procedures. How a simulation model is designed can enable, inhibit, or even invalidate analytical procedures and methodology research results.

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Metadata

Authors
Schruben, L.
Venue
ACM Transactions on Modeling and Computer Simulation
Published
2010-01
Volume
20
Issue
1
Pages
1-22
ISSN
  • 1049-3301 (ISSN-L)
  • 1558-1195
OpenAlex
W1992870153
Cited by
895
References
0
FWCI
79.36
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Simulation modeling for analysis. https://app.cochat.ai/papers/10.1145/1667072.1667074
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Schruben, L. (2010). Simulation modeling for analysis. ACM Transactions on Modeling and Computer Simulation. https://doi.org/10.1145/1667072.1667074

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.