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

Abstract

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.

Determining Priorities in Infrastructure Management Using Multicriteria Decision Analysis

“…The TOPSIS method used in this research is based on clear numbers. In future research, it is possible to apply intuitionistic fuzzy sets (IFS) to the maintenance management problem of infrastructural elements according to [25] to increase the accuracy of the decisions made by the involved stakeholders and thus even more realistically simulate the decision-making process with a certain degree of uncertainty. In this case, the TOPSIS method is very suitable because it allows for extensions, and according to [45], it also provides support for interval or fuzzy criteria, interval or fuzzy weights, uncertainty, and lack of information, or vagueness.…”

“…Salimian et al [25] presented an integration of approaches for obtaining criteria weights and ranking alternatives. Criteria weights were calculated using a combination of the CRITIC method and the ideal point method while alternative ranks are calculated by integrating the evaluation based on distance from average solution (EDAS) and additive ratio assessment (ARAS) approaches under uncertainty.…”

A Hybrid TOPSIS-Structure Entropy Weight Group Subcontractor Selection Model for Large Construction Companies

“…TOPSIS has many advantages, including broad applications, simple calculations, and full utilization of information in the decision-making matrix [30,31]. Because of these advantages, many construction researchers utilized TOPSIS for various construction decision-making applications [32,33].…”

Integrating Combination Weighting of Game Theory and Fuzzy Comprehensive Evaluation for Selecting Deep Foundation Pit Support Scheme

“…In order to solve this problem, there is an urgent need to adopt scientific decision-making methods and comprehensively consider the key factors that may affect decision making, so as to provide an objective theoretical basis for scheme selection [8,9]. The multi-criteria decision-making (MCDM) method is widely used in different research fields and it can provide a logical framework, comprehensive evaluation, and comparison of various schemes, so that decision makers can choose more comprehensively and objectively [10]. Temiz and Calis [11] used AHP and the preference ordering organization method (PROMETHEE) to consider the fixed and quantitative indexes, rank the alternative schemes, and select the appropriate excavator for a construction site; Shahpari et al [12] used Decision-making Trial and Evaluation Laboratory (DEMATEL) to determine the influence degree of each criterion, and then determine the index weight by the Analytic hierarchy process (AHP).…”