Project managers are challenged to continuously make decisions throughout the development of a project attempting to minimize the overall project cost and, at the same time, seeking to accomplish a pre-established deadline. These time-cost tradeoff decisions are made even more complex when resource constraints, caused by limited available resources, are added to the equation. The goal of this research is to design a simulation-based optimization approach to solve the resource constrained project scheduling problem (RCPSP) under uncertainty. Two methods are proposed: the Total Cost Resource Constrained Method (TCRCM) and the Earned Value Resource Constrained Method (EVRCM). The TCRCM seeks to minimize the total project cost, including activity and penalty costs due to lateness at project completion, while considering the RCPSP with stochastic activity times and costs in terms of resource alternatives as well as precedence relationships for activities sharing resources. The EVRCM, which is based on earned value management, not only considers penalty costs at project completion, but at several project milestones along the execution of the project. Both methods can be implemented in two phases: Phase I, and Phase II. Phase I is implemented prior the start of the project to determine the optimal resource configuration for the entire project based on the specified performance measure (e.g. total project cost). Phase II is implemented as the project progresses to determine the optimal resource configuration for the remaining activities of the project. The robustness of both methods is evaluated through a set of experiments. Lastly, the methods are integrated into Microsoft Excel
