Multi-Project Scheduling with Uncertainty and Resource Flexibility: A Narrative Review and Exploration of Future Landscapes

This paper presents a narrative review on the Resource-Constrained Multi-Project Scheduling Problem (RCMPSP) under uncertainty and resource flexibility. Traditional project scheduling assumes complete information and a deterministic environment where a pre-computed baseline schedule is executed. However, real-world projects frequently face uncertainty, such as variable task durations and fluctuating resource availability. Analyzing studies from 2013 to 2024, this review examines optimization models addressing multiple objectives, including minimizing project duration, cost, and resource leveling. It categorizes solution approaches, from exact algorithms to heuristic and metaheuristic methods, while reviewing the primary instance sets and benchmarks used in the field. Additionally, it highlights the value of flexible resource management approaches that enable adaptive responses to real-time project demands, thereby enhancing scheduling robustness. By systematically addressing RCMPSP under uncertainty, this paper provides a valuable framework for researchers and practitioners seeking to develop resilient, adaptive scheduling solutions for complex, dynamic project environments.