About this chapter
A stochastic system need not always be approached through a discrete-event simulation. Burk introduces analytical models, including Markov chains and queueing models, as alternatives worth considering before committing to a more elaborate computational representation. The chapter compares the assumptions, effort, and kinds of results associated with these approaches. Analytical tractability comes with restrictions; simulation offers flexibility but produces sampled behavior that must be interpreted. Readers can use this comparison to ask which details a model needs to retain and which simplifications are defensible for the question being asked, rather than treating additional model detail as an automatic improvement.
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Companion reading noteStructuring a decision under uncertaintyCite this contribution
Roger Chapman Burk. (2024). Analytical Modeling of Stochastic Systems. In Natalie M. Scala & James P. Howard, II (Eds.), Handbook of Military and Defense Operations Research (2nd ed., pp. 183–204). Chapman & Hall/CRC. https://doi.org/10.1201/9781003396307-8
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