The results of the sensitivity analysis.

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.当前，项目组合选择问题是众多建筑企业，尤其是项目型建筑企业的重要管理任务之一。另一方面，受项目评价复杂度较高与资源约束有限的双重影响，项目组合选择往往面临诸多挑战。本研究旨在针对项目型企业的项目组合选择问题，提出一种融合聚类与决策的全新方法。该集成方法涵盖用于项目聚类的K-means聚类算法（K-means）、用于确定指标优先级的SWARA法（SWARA），以及用于研究企业项目排序与遴选的MULTIMOORA法（MULTIMOORA）。此外，为验证方法有效性，本研究将MULTIMOORA法的决策结果与WASPAS法（WASPAS）的结果进行了对比。首先，本研究通过文献调研与专家研判，选取5项一级指标（含18项二级指标）用于项目组合的聚类与排序。随后，基于上述指标与二级指标设计问卷，收集本研究所需的实验数据。基于实验结果，本研究将25个待选建筑项目划分为4个聚类并完成对应排序。研究结果表明，所提出的集成方法可通过基于选取的一级与二级指标对项目组合进行排序，实现项目组合的聚类与最优组合筛选。同时，研究发现仅基于5项一级指标的排序结果，与基于18项二级指标的排序结果存在显著差异；结合二级指标的特性，以及在MULTIMOORA方法应用中关注指标/二级指标可取性与非可取性的重要性，基于二级指标的排序结果更具合理性与应用价值。