An Integrated Multi-Criteria Decision Model to Select Sustainable Construction Projects under Intuitionistic Fuzzy Conditions

被引:9
|
作者
Salimian, Sina [1 ]
Mousavi, Seyed Meysam [1 ]
Tupenaite, Laura [2 ]
Antucheviciene, Jurgita [2 ]
机构
[1] Shahed Univ, Dept Ind Engn, Tehran 3319118651, Iran
[2] Vilnius Gediminas Tech Univ, Dept Construct Management & Real Estate, LT-10223 Vilnius, Lithuania
关键词
sustainable construction projects; MCDM method; intuitionistic fuzzy sets; CRITIC method; ideal point approach; ARAS method; EDAS method; RISK-ASSESSMENT; MCDM; SAFETY; AHP; RANKING; SYSTEM; TIME;
D O I
10.3390/buildings13040848
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Choosing a proper construction project is a vital subject for entrepreneurs to reduce their costs. In real cases, vagueness and uncertain data drive decisions based on uncertainty. The intuitionistic fuzzy sets (IFSs) theory could assist decision-makers (DMs) in inscribing inadequate knowledge. Nevertheless, this paper provides a new integrated decision analysis model with IFSs. The suggested procedure includes a new decision flow under uncertain situations to define the significance of criteria. In this regard, the weighting of subjective DMs is required for this manner; the only input data needed are an alternative evaluation matrix. Then, a case study on sustainable energy project selection is explained to show the purpose of the suggested model. In this regard, four main criteria, technological, economic, social, and environmental, and seven alternatives from different kinds of energies are introduced to select the appropriate energy project. In this model, the weights of criteria are defined based on a new combined method based on two CRITIC and ideal points approaches. The proposed soft computing model computed the ranking of main alternatives by integrating the ARAS and EDAS approaches; the final outcomes indicate that the second alternative has higher values than other alternatives concerning nuclear energy. Afterward, sensitivity and comparative analyses are generated to determine the efficiency and validity of the proposed model. The sensitivity analysis changes the criteria weights. The comparative analysis compares the IF-TOPSIS method and the proposed model and computes the different degrees to confirm the efficiency of the introduced soft computing model.
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页数:21
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