Using GERT to Model and Estimate the Success Probability of Stochastic Projects Under Rework

In practice, rework is a major threat to projects’ performance and increases the risk of not delivering the outcomes on time and on budget. The classical project scheduling methods are incapable in considering the rework and stochastic structure for projects in planning phase. The current study models the stochastic projects through a GERT network in which occurrence of rework is allowed. The aim is to find the optimal execution mode for each activity in a way that the project completes within a desire time and the resource constraint is satisfied. We develop a multi-mode time-cost trade-off resource constraint project scheduling problem under uncertainty to find a here-and now solution to minimize project completion time. The problem is solved using a combination of flow-graph theory, Mason’s rule and Monte-Carlo simulation method. To represent the efficiency of proposed solution methodology, a stochastic numerical experiment is generated and the obtained results show the capability of the solution method.