## 5 Discussion and Findings  
The main goal of this section is to provide an insightful analysis of advancements in multi-project scheduling under conditions of uncertainty and resource flexibility. A brief description of them was presented in Section 2, and in the following section achievements will be reported for each of them. Key findings are organized around the major objectives in this domain, such as minimization of project makespan, minimization of project cost, or resource leveling. Overall, while minimization of project delay or project makespan is not always considered an objective in papers about RCMPSP, some papers take it into account and propose novel algorithms or models to optimize it, along with other objectives such as minimization of project cost. This is because delay, which refers to the amount of time by which a project is postponed or extended beyond its original due date, is often seen as a result. \begin{table}
\begin{tabular}{c c} \hline \hline
**Instances** & **Research Works** \\ \hline Generated instances & [26, 28, 29, 31, 32, 39, 48, 49, 50, 52, 56, 60, 61, 63, 64, 67, 68, 71, 72, 80, 94, 95] \\ Problem examples & [42, 58, 65, 74, 78, 85] \\ Real-world instances & [14, 15, 33, 37, 38, 43, 44, 45, 53, 57, 62, 69, 75, 76, 81] \\ MPSPLIB & [2, 24, 41, 46, 51, 66, 70, 93] \\ PSPLIB & [3, 7, 16, 21, 28, 36, 45, 52, 54, 57, 58, 84, 85, 86, 88, 97] \\ PostgreSQL & [73] \\ MMLIB & [30, 77] \\ MPLIB1 & [25] \\ MPIIB2 & [23] \\ MISTA 2013 & [34, 40] \\ iMOPSE & [79] \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Research works that address benchmarks. Figure 8: Percentage of research on a different set of instances. This section provides a detailed analysis of the studies reviewed in earlier sections, focusing exclusively on those addressing real-world-based case studies, to survey the gap between theoretical approaches and practical applications concerning the RCMPSP and related variants. Table 8 presents research developed in real environments, highlighting the significance of this problem within the industrial sector. Column 2 shows the application domain. Columns 3-5 show the dimensions of the scenarios handled by each case in terms of the maximum number of projects, the maximum number of activities, and the maximum number of different resources considered. Following the categorization provided in Section 4, columns 6-10 report the objective functions. Additionally, to analyze the different objective functions applied in real environments, this table shows the applications in the manufacturing field that are the most representative ones, while 15 real-world-based cases are examined. The most used objectives are related to time-based objective functions. Based on the reported works, it can be observed that makespan minimization is the most used one, followed by minimization of total project cost. To provide a broader perspective, a separate table (Table 9) was compiled in which the key contributions, strengths, weaknesses, and future suggestions of some related studies were randomly reviewed. Through this comparative analysis, existing research gaps are identified, and the novelty and relevance of the proposed approach are clarified. In this  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Instance**} & \multicolumn{6}{c}{**Objective Functions**} \\ \cline{2-10}
**Research** & & & & & & **Rsrc. ** & & **Time** & \\ \cline{3-10}
**Works** & **Domain** & **\# Proj. ** & **\# Activities** & **\# Rsrc.