Efficient Estimation of Arc Criticalities in Stochastic Activity Networks

R. A. Bowman
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R. A. Bowman: Union College, Graduate Management Institute, Bailey Hall, Schenectady, New York 12308

Management Science, 1995, vol. 41, issue 1, 58-67

Abstract: An algorithm is described for estimating arc and path criticalities in stochastic activity networks by combining Monte Carlo simulation with exact analysis conditioned on node release times. These estimators are proved to be unbiased and to have lower variance than the corresponding standard Monte Carlo estimators. The algorithm is applied to a variety of standard and randomly generated test networks to establish that the estimators are significantly and robustly more efficient than the standard estimators when run time and statistical efficiency are properly combined.

Keywords: project management; simulation; conditional estimators (search for similar items in EconPapers)
Date: 1995
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:41:y:1995:i:1:p:58-67

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