Abstract
In fields such as construction engineering, maintenance services, and globalized manufacturing, enterprises widely adopt a distributed management mode to coordinate and manage multiple projects sharing global resources. Under this management mode, the distributed resource-constrained multi-project scheduling problem (DRCMPSP) has gradually become a core issue in both project management practices and academic research. This article investigates the intricacies of global resource uncertainty within the DRCMPSP framework, meticulously portraying resource failures through a scenario-oriented approach. With the aim of obtaining a high-quality baseline schedule and adeptly countering the consequences of global resource failures, a comprehensive two-phase DRCMPSP planning-repairing model is established. Additionally, a heuristic algorithm, grounded in a Graded Scoring Rule (GSR) and Repairing Graded Scoring Rule (RGSR), is proposed to solve the model. Extensive simulation experiments carried out on the MPSPLIB problem library demonstrate that the GSR/RGSR excels in handling large-scale instances. As global resource conflicts increase, the competition among projects for resources intensifies, and the utilization of GSR/RGSR proves to be significantly more effective in mitigating project delays and reducing stability costs in comparison to other rules. Furthermore, the GSR/RGSR demonstrates remarkable adaptability to variations in problem size and resource conflict intensity, delivering more consistent and dependable optimization outcomes.
Published Version
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