Intuitionistic fuzzy EM-SWARA-TOPSIS approach based on new distance measure to assess the medical waste treatment techniques

Abstract

Due to the potential harm to public health as well as the environment, medical waste treatment have emerged as a critical concern, especially in developing nations. The selection of a suitable medical waste treatment technique (MWTT) is now characterized as a critical multi-criteria decision-making (MCDM) problem because of the incorporation of several competing criteria. This study provides a hybrid MCDM technique for assessing MWTTs concerning social, environmental, economic, and technical criteria in an intuitionistic fuzzy environment. The intuitionistic fuzzy set (IFS) is a potent tool for expressing ambiguous and vague information efficiently and has proven effective for MCDM problems. In IFS environment a new distance measure and an entropy measure (EM) are introduced by employing the generalized Csiszar f-divergence measure, which are further used to construct the MCDM algorithm. The introduced entropy measure is used to examine the objective weights of criteria, and the distance measure is employed to construct the technique for order performance by similarity to ideal solution (TOPSIS) for the assessment of the alternatives. Furthermore, the significance of the criteria for the proposed MCDM technique is evaluated by integrated weights (combining objective and subjective weights). The Stepwise Weight Assessment Ratio Analysis (SWARA) technique is used to obtain the subjective weights for criteria. Thus, a hybrid MCDM technique, namely IF-EM-SWARA-TOPSIS, is developed. To exhibit the effectiveness and applicability of the suggested framework, a MWTT selection problem in Indian context is depicted. The comparative study and sensitivity assessment are conducted to show the sustainability and stability of the proposed IF-EM-SWARA-TOPSIS technique for ranking the preference order of the MWTTs. Moreover, the practical implications of the proposed method are discussed.