PHASED CAPACITY EXPANSION - USING CONTINUOUS DISTRIBUTIONS TO MODEL PRIOR BELIEFS

Abstract

Many current equipment replacement/production capacity expansion decisions carry increasing amounts of performance uncertainty when the alternative processes include technical innovations. In a sequential decision making environment, post-audit information can be used to resolve this uncertainty. In this paper, we demonstrate how three-point, PERT-type estimates can be used to determine continuous prior probability distributions that incorporate the post-audit information in Bayesian revision. Further, we develop the concept of equivalent sample size to insert qualitative judgment into the decision making process. This is initially used to reflect our belief in the estimates' quality, and, subsequently, in an assessment of the quality of the observed sample data. A case study of an actual decision problem is used to illustrate the concepts.

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