A novel method based on clustering and decision-making for construction project portfolio selection

Nowadays, the problem of project portfolio selection is one of the important tasks in many construction organizations, especially project-based ones. On the other hand, project portfolio selection usually faces many challenges due to the complexity of project evaluation as well as limited resources. The present research aims to present a new method based on clustering and decision-making for project portfolio selection in project-based companies. The proposed integrated method includes the K-means method for clustering projects, the SWARA method for prioritizing the identified criteria, and the MULTIMOORA method for ranking and selecting the projects of the studied company. In addition, the results of the MULTIMOORA method was compared with the results of the WASPAS method for verification. First, five criteria (including 18 sub-criteria) were selected using literature review and expert judgment for clustering and ranking project portfolios. Then, the research data was collected from a questionnaire containing identified criteria and sub-criteria. Based on the obtained results, 25 available construction projects were placed and ranked in 4 clusters. The findings show that the proposed integrated method was able to cluster the project portfolios and select the best project portfolios by ranking the project portfolios based on the identified criteria and sub-criteria. Also, the findings indicate that the rankings using five main criteria were different from the rankings using 18 sub-criteria, and therefore due to the nature of the sub-criteria and the importance of paying attention to the "desirability or undesirability of the criteria/sub-criteria in using the MULTIMOORA", the rankings using the sub-criteria were more preferable.