Generating beta random rate variables from probabilistic estimates of fireline production times

J. Gilless () and Jeremy Fried ()

Annals of Operations Research, 2000, vol. 95, issue 1, 205-215

Abstract: An extension of probabilistic PERT/CPM is proposed as a framework for soliciting expert opinion to characterize random variables for stochastic treatment in simulation models. By eliciting minimum, modal, ninetieth percentile, and maximum estimates, the distribution of variables with probability density functions of beta form can be explicitly characterized without relying on the traditional, but empirically unverified, assumption of a standard deviation equal to one-sixth of the range. This practical and inexpensive technique is illustrated by application to a wildfire protection planning problem – estimating the time required to produce a given length of fireline by different firefighting resources under diverse conditions. The estimated production times are an essential input to a planning model of initial attack on wildland fires used by the California Department of Forestry and Fire Protection, and provide that agency with useful “rules-of-thumb” for use in firefighter training. Copyright Kluwer Academic Publishers 2000

Keywords: expert opinion; stochastic simulation; fire control (search for similar items in EconPapers)
Date: 2000
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DOI: 10.1023/A:1018945906565

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