## 1 Introduction  
In realistic scheduling situations, companies typically manage multiple projects concurrently rather than a single one [1]. This transition from single-project to multi-project management introduces a significant layer of complexity to the scheduling process. The scheduling process becomes more challenging in this multi-project case, as some resources might need to be shared across multiple projects (e.g., facilities, machines, human resources). This resource dispute gives rise to intricate scheduling challenges, as decisions made for one project can have cascading effects on the timelines and budgets of others. The study of these complexities and the development of effective methodologies to navigate them is known as the Resource-Constrained Multi-Project Scheduling Problem (RCMPSP) [2].  
The RCMPSP aims to optimize allocation of resources across multiple projects while adhering to project-specific constraints, such as activity precedence relationships and deadlines. However, the inherent assumption of deterministic conditions--where activity durations, resource availability, and project parameters are known with certainty--underlies many traditional RCMPSP models. This assumption is a significant oversimplification of real-world project environments, which are characterized by a high degree of uncertainty.  
During project execution, random events such as activities taking different durations than expected, introducing new projects, and resources being unavailable cause production instability and significant delays. Therefore, these uncertainties must be considered in project scheduling.  
To increase flexibility, workloads corresponding to each activity can be defined, and resource requirements can be adjusted flexibly. This approach, rooted in the concept of the Flexible Resource Constrained Project Scheduling Problem (FRCPSP) [3], has led to the development of several models/methods aimed at optimizing resource allocation under uncertainty [4], with further exploration into resource flexibility [5; 6; 7; 8]. This paper looks closely at both uncertainty and flexibility with RCMPSP. Therefore, the two main contributions of this paper are (i) a comprehensive review of the literature analyzing and discussing the characteristics and objective functions proposed so far for the RCMPSP, as well as solution methods and existing benchmark datasets; and (ii) an examination of the main trends over the last 12 years, along with insights into how the RCMPSP is applied in real-world environments, helping to point out future research directions. The structure of this paper is organized as described below.  
The findings of this research will offer valuable guidance for both researchers and practitioners in multi-project scheduling. By synthesizing the existing body of knowledge and highlighting key research gaps, it seeks to advance the development of more effective, resilient, and practical scheduling methodologies for multi-project environments.  
Section 2 provides the background. In Section 3, the methodology used to carry out this research is described. In Section 4, a review of resource characteristics and the variants used to address the RCMPSP is explored. Discussion and findings are presented in Section 5, and finally, the conclusion appears in Section 6.