Dynamic Optimization of the Multi-Skilled Resource-Constrained Project Scheduling Problem with Uncertainty in Resource Availability

Multi-skilled resources have brought more flexibility to resource scheduling and been a key factor in the research of resource-constrained project problems. However, existing studies are mainly limited deterministic problems neglect some uncertainties such as breakdowns, while availability may change over time due unexpected risks COVID-19 pandemic. Therefore, this paper focuses on multi-skilled problem with uncertainty availability. Different from previous assumptions, allowed switch their skills, which we call dynamic skill assignment. For complex problem, nested algorithm called GA-PR is proposed, includes three new priority rules improve solving efficiency. Moreover, algorithm’s effectiveness verified by an example, modified Project Scheduling Problem Library (PSPLIB) used for numerical experimental analysis. Numerical experiments show that when considered, skills has supplied, better method performs; other hand, higher probability unavailability required, worse performs.The results helpful improved decision making.