PERT-IA : a new heuristic for schedule risk analysis in project management -

Abstract

The delay in a project schedule is a serious problem, and almost all projects suffer from such delays whether they are small, medium, or large. Delays might cause financial losses especially in big projects. The question is why this problem is still there, with all the advancements in project scheduling techniques? One important reason seems to be related to the methods that are utilized in analyzing project schedules such as CPM and PERT, which fail to capture the risk accurately. This thesis attempts to estimate the probability of a project being late by accounting for the topology of the whole project network instead of just looking at one path, as in CPM or PERT. The method we develop, PERT-IA, is a hybrid of PERT, which considers the path with the longest duration, and an independence analysis (IA) that assumes that all paths of the network have independent durations. The method estimates the lateness probability, a project being late for a set of deadlines as a weighted average of that from PERT and IA, with the weight on PERT being high for project networks having paths exhibiting high commonality (i.e., have many common activities). Results in this thesis show that using PERT-IA improves schedule risk analysis, over PERT, by yielding better estimates of the probability of being late. This is validated using Monte Carlo simulation.