Project scheduling problem integrated with resilient material procurement: a two-stage stochastic optimization approach

Traditional project scheduling approaches often overlook the complexities of material logistics; however, material procurement uncertainty arising from supplier disruptions introduces significant risks to project completion, resulting in delays and additional costs. This study proposes a mathematical model that integrates project scheduling and material procurement under uncertainty, incorporating resilience strategies to mitigate disruptions. The model explicitly considers backup warehouses at the project site, alternative suppliers, and supplier-based storage facilities to enhance the robustness of the supply chain. Additionally, it accounts for fluctuations in supplier capacity and uncertain lead times. Beyond minimising costs and project duration, the model also incorporates sustainability objectives, ensuring environmentally and socially responsible procurement decisions. To address uncertainty effectively, two-stage stochastic programming is employed, optimising decisions across multiple scenarios. The model is validated through a case on locomotive brake cylinder manufacturing and solved using the augmented epsilon-constraint method. In addition to the case study, two additional datasets were examined to enhance the validity and accuracy of the results. The findings indicate that considering the backup warehouse, supplier’s warehouse, and backup supplier improves project scheduling efficiency and reduces financial risks. Moreover, the scenario-based framework provides more adaptive and robust planning, ensuring optimal responses to disruptions.