PSM: A New Approach to Probabilistic Scheduling

A new scheduling method, where probability values can be assigned to activity durations, is proposed in this thesis. Probabilistic Scheduling Method (PSM) accepts activity durations tagged with probability or confidence intervals. Tests were carried out using examples of 3,7, and 9 activities to evaluate PSM's practical capability. The comparisons of PSM to Critical Path Method (CPM), Performance Evaluation and Review Technique (PERT), and Monte Carlo application to PERT (MC PERT) conclude that PSM results in similar most probable duration estimation. Further tests were implemented to evaluate PSM's capability to project schedule revision on an ongoing project. A microsoft Excel application was used to organize tests data and calculations. PSM computations are more industry friendly. They allow for a range of duration associated with a range of probabilites. PSM provides flexibility and simplicity, and also dependency information that will benefit its user in decision making