LAUSR

Abstract This article addresses the project scheduling and the materials ordering problem (PSMOP) with uncertain activity durations. A two-stage optimisation approach is proposed to generate a robust schedule in order to protect the project execution from the duration uncertainty. First of all, a mixed-integer programming model under a deterministic environment is formulated to address this issue, which aims to minimise the corresponding costs and is solved by the genetic algorithm (GA). Second, a robust project scheduling integrated with materials ordering method (RPSMOM) is developed to build a proactive schedule on the basis of the baseline schedule generated by the given deterministic model. In this method, a novel index that measures the risk of activity delay (RAD) is suggested by taking the uncertain activity durations into account. Finally, computational experiments are conducted under different levels of activity duration uncertainty. The results demonstrate that the integrated proactive scheduling method is highly effective in decreasing the total cost and improving the robustness of the project schedule in most circumstances.