The proactive and reactive resource-constrained project scheduling problem

Uncertainty has become an inevitable aspect of project scheduling. We study the resource-constrained project scheduling problem (RCPSP) with stochastic durations. One of the most studied approaches to deal with stochastic durations is that of proactive and reactive scheduling. In this paper, we formulate an integrated proactive and reactive scheduling problem with a combined cost function which includes a baseline schedule cost as well as costs of a series of reactions. We propose four dynamic programming based models (Models 1-4) that solve the problem until optimality over different classes of policies. We compare our models with each other and with a combination of a traditional proactive solution (STC) and a reactive solution (RP SGS). Computational results show that Model 2 outperforms the traditional solution only when reaction costs are greater than zero. Moreover, Model 3 and Model 4 clearly outperform Model 1 and Model 2 in all settings and the traditional solution in most of the settings.