Multicriteria group decision making approach based on an improved distance measure, the SWARA method and the WASPAS method

The concept of intuitionistic fuzzy set (IFS) has extensively used to handle the uncertainty of real-life decision making problems. The aim of this study is to propose an integrated multicriteria group decision making (MCGDM) approach with intuitionistic fuzzy information and apply to select the most suitable renewable energy source with respect to multiple aspects of sustainability criteria. For this purpose, we firstly propose an improved distance measure to quantify the degree of difference between IFSs. Some numerical examples are presented to show the effectiveness of the proposed measure over the existing distance measures under the context of IFS. Further, we develop a weighting approach to find the criteria weights, which combines the objective weighting model using improved distance measure and the subjective weighting model using stepwise weighted assessment ratio analysis (SWARA) with intuitionistic fuzzy information. Based on the proposed criteria weighting model, we develop an integrated weighted aggregated sum product assessment (IF-WASPAS) approach for solving MCGDM problems under intuitionistic fuzzy environment. To prove the applicability and efficacy of the developed approach, we implement it on a case study of renewable energy source selection problem with multiple aspects of sustainability including technical, socio-political, environmental, and economic perspectives. Moreover, the sensitivity and comparative analyses are discussed to examine the feasibility and steadiness of introduced approach in order to assess the RES options. In this paper, we present an improved decision making approach, which makes a significant contribution to the renewable energy sources evaluation process with uncertainty.