Research On Resource-Constrained Project Portfolio Selection And Scheduling Problem Under Uncertainty

This research is related with the topic of resource-constrained project portfolio selection and scheduling problem under uncertainty. As an important part of project management, project portfolio selection and scheduling problem have gradually attracted attention both theoretically and practically. Facing the increasing market fierceness and limited company resource ability, project managers must find an optimal project portfolio and control the risks occurring during the project execution. Meanwhile, unpredictable fluctuations and increasing fierceness of market economy are in parallel with high uncertainty. Therefore, it’s necessary to discuss the project portfolio selection and scheduling problem under uncertainty, to find a suitable project portfolio and project schedule with the limit of time and resource.In previous studies, most scholars have paid attention to project selection or project plan separately, ignoring the link between these two important problems of project management. What’s more, most of analysis on the interaction of these two factors are not under uncertainty, which tends to misestimate the value of project portfolio and project plan.This study is aimed at applying the robustness theory to the evaluation of project portfolio selection and project scheduling problems under uncertainty. By linking project portfolio selection with project scheduling, this study seeks to maximize the profit and minimize the risk of optimal project portfolio and find the project schedule with robustness by minimizing the project delay probability.A double-decision method is designed to solve this problem, which means the project scheduling under uncertainty is the sub-problem of project portfolio selection. In order to solve the problem, genetic algorithms (GA) are used to solve the project portfolio selection problem and starting time criticality (STC) heuristics are applied to solve multi-project scheduling problem. Monte-Carlo heuristics are used to deal with the uncertainty of project profit, which shows the interaction of project portfolio selection and project scheduling under uncertainty With the experiment design method, project portfolio selection and project scheduling problem instances are applied to test effectiveness of the algorithm. The results indicate that the model and algorithms have an optimal solution for solving project portfolio selection and project scheduling problems under uncertainty.