The stochastic time-cost tradeoff problem: A robust optimization approach

We consider the problem of allocating resources to projects performed under given due dates and stochastic time–cost tradeoff settings. In particular, we show how to implement a state-of-the-art methodology known as “robust optimization” to solve the problem. In contrast to conventional approaches, the model we develop results in management policies rather than optimal values for the original decision variables. Hence, the project manager can postpone decisions to the point of time when they are actually required and then make them according to the optimal policy (which employs cumulative data on the project progress). The solutions are guaranteed to be robust—that is, ensuring feasibility except when the uncertain parameters assume extreme values. Still, as we demonstrate through an extensive numerical example, the price we need to pay to obtain that robustness is relatively small even for high uncertainty levels. © 2006 Wiley Periodicals, Inc. NETWORKS, Vol. 49(2), 175–188 2007