Neglecting uncertainties in the estimation of activities, costs, and durations can significantly contribute to overruns in a project's budget and schedule. On the other hand, properly enforced penalties and incentives can motivate contractors to finish on time and within the allotted budget. However, the current literature on this topic does not sufficiently address project penalties and incentives within the context of uncertainty and dependence. Thus, this dissertation considers how allocating penalties and incentives can impact a stochastic project network in which activity durations are random variables, and some of the activities are subcontracted. The impact of penalty/incentive schemes on project and activities uncertainties is also examined. Overall, one of the main pursued benefits of this work is to provide project stakeholders with a tool that can help determine the appropriate penalty and incentive rates for outsourced activities when creating the contract. The study revealed that a total allocation of a project level penalty/incentive to relevant activities was considered a fair allocation. A Monte Carlo Simulation model (MCS) was used to generate random variables, incorporate activity distributions, incorporate dependence uncertainties, and to examine the effect the penalty/incentive scheme has on the aggregated project cost. In order to validate the simulation model, its outcomes were verified with deterministic outcomes. Furthermore, based on the several allocation methods explored, the most adequate allocation method found was the normalized allocation of project penalty/incentive to activities based on the probability of a zero slack activity lying on the critical path. The presented MCS model was then expanded and applied on a larger network. The results of this study demonstrated that the penalty/incentive scheme can increase the project uncertainty at earlier stages of the project, but by using the proper allocation method at later stages, it is contained to the baseline levels that do not comprise any penalty/incentive. The study also revealed that the common practice of assuming project activities as being independent underestimates the most critical, not the least critical, activities' penalty/incentive rates.
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