Managing Portfolios of Projects Under Uncertainty with Application to Construction Activities

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Projects are often undertaken in an environment of considerable uncertainty. Uncertainty may be reflected in the duration and outcomes of specific tasks, as well as in the effectiveness of resources applied to them. Project and program managers must decide, in these uncertain conditions, how to allocate and manage scarce resources across many projects that have competing needs. The construction industry is one in which this need is particularly acute. Today, project planning and scheduling is done using algorithms that either ignore the resource constraints and consider uncertainty in task duration, or ignore the uncertainty in task duration and focus on resource-constrained scheduling.This research focuses on developing new computationally tractable modeling tools for allocating resources under uncertainty in realistic multi-project planning and scheduling environments. A key aspect of the mathematical approach we are using is that it provides an explicit mechanism to evaluate the tradeoff between the planned schedule for a project (or portfolio of projects) and the level of risk that the schedule will become infeasible (as a result of uncertainties in the task durations and outcomes). This research has obvious application to construction projects, as well as to many other industrial, commercial and public sector applications. Our approach will create significant new tools for use by project and program managers in many types of undertakings. Furthermore, since the need to work in the presence of uncertainty is a critical element of engineering practice, it is important to provide students with an exposure to project management under uncertainty. To this end, we will develop cases studies and a master of engineering project based on the research described in this proposal. Those case studies and project will support education in three programs: undergraduate civil engineering, and the Master of Engineering programs in engineering management and systems engineering.