In this paper, we extend the multi-skilled resource-constrained multi-project scheduling problem (MSRCMPSP) by introducing the concept of multiple project types (MSRCMPMTSP). The study considers two categories of projects: investment projects, which generate positive net present values (NPVs), and mandatory projects, which result in negative NPVs but are required to be executed. To solve this problem, we employ a priority rule-based heuristic approach. Specifically, forward scheduling is applied to projects expected to yield positive NPVs, whether they are optional or mandatory. In contrast, backward scheduling is used for projects with negative NPVs, as this strategy minimizes the impact of excessive negative NPVs. The dataset for this study is constructed using the design of experiments (DoE) methodology, enabling a comprehensive evaluation of the proposed heuristic. We compare the performance of our approach against randomly generated schedules through extensive simulations. The results indicate that the heuristic is effective in addressing the MSRCMPMTSP.