A two-layer approach for solving robust decentralized multiproject scheduling problem with multi-skilled staff

Uncertain activity durations and multi-skilled staff allocation are two practical factors that are difficult to cope with in real project management. This paper studies a new decentralized resource-constrained multiproject scheduling problem with uncertain activity durations and multi-skilled staff allocation. The robust project scheduling is employed to tackle uncertainty. We name it the robust decentralized resource-constrained multiproject scheduling problem with multi-skilled staff (RDMPSP-MS). To formulate this problem, a two-layer model containing local scheduling and global coordination decision-making is established based on the multiagent system. To solve this model, a two-layer approach (TLA) is developed. In the TLA, a starting time criticality heuristic method is adopted to handle the local scheduling problem, and a global resource allocation heuristic algorithm is designed to allocate multi-skilled staff. The computational experiments are conducted on the adapted Multi-Project Scheduling Problem LIBrary (MPSPLIB) data set. The results show that the proposed TLA outperforms seven heuristic algorithms based on priority rules regarding solution quality and efficiency on most problem subsets. It is further verified that the robustness of the baseline schedule deteriorates with the increase in problem size and activity duration variability level. Additionally, the results of this research provide practical guidance for managers who expect to determine reasonable project deadlines in a decentralized multiproject environment.