Interval-valued pythagorean fuzzy power average-based MULTIMOORA method for multi-criteria decision-making

MULTIMOORA Method-Based Schweizer–Sklar Operations for CO2 Geological Storage Site Selection Under Pythagorean Fuzzy Environment

The site selection of CO₂ geological storage facilities is essential for the development of safe and efficient carbon capture, utilization, and storage (CCUS) projects. Normally, CO₂ geological storage site selection can be regarded as a complex multi-criteria decision-making (MCDM) problem. The aim of this paper is to present an integrated decision-making method for solving the site selection problem for CO₂ geological storage. To achieve this goal, this method is based on multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) method and prioritized aggregation operators in Pythagorean fuzzy environment. The academic contributions of this study include: first, some Pythagorean fuzzy Schweizer–Sklar prioritized aggregation (PFSSPA) operators are proposed, which take into account the priority levels of criteria and the risk preferences of decision makers. The excellent properties of these operators are given. Then this study extends the classical MULTIMOORA method based on the developed aggregation operators (named PFSSPA-MULTIMOORA), and the calculation process of this method is described in detail. Subsequently, on the basis of the constructed criteria system, the PFSSPA-MULTIMOORA method is applied to rank the alternatives. Finally, we successfully utilized the PFSSPA-MULTIMOORA method to solve the site selection problem of CO₂ geological storage in China. A comparative analysis of existing methods verifies the effectiveness and robustness of the proposed method. This work can provide advanced decision support for researchers and practitioners.

Selection of third party reverses logistic providers: an approach of BCF-CRITIC-MULTIMOORA using Archimedean power aggregation operators

One of the most powerful tools to operate imprecision is bipolar complex fuzzy sets (BCFSs), which is an enlargement of bipolar fuzzy sets (BFSs) as well as complex fuzzy sets (CFSs). This paper deals with an integrated MULTIMOORA (multi-objective optimization on the basis of ratio analysis plus full multiplicative form) framework as a generalization of fuzzy MULTIMOORA procedure to assess the multi-criteria decision-making (MCDM) problems with BCFSs. We develop BCF-Archimedean power weighted (ordered weighted) arithmetic and geometric aggregation operators (AOs) and discuss their properties from this point of view. The proposed Archimedean power-weighted AOs can eliminate the influence of extreme evaluating criteria values from some biased experts with different preference attitudes under the BCF setting. Afterward, we put forward an integrated MULTIMOORA algorithm based on the proposed AOs, where criteria weights are estimated using the CRITIC (criteria importance through inter-criteria correlation) method, which is a well-known objective weighting method based on aggregated score values of options, intensity contrast of every criteria and conflict among attributes. In the proposed methodology, criteria values are aggregated based on the MULTIMOORA method that involves three sub-methods: the ‘ratio system’, the ‘reference point’ and the ‘full multiplicative form’ and thus takes less computational time, minimum mathematical evaluations and bears good stability. In the following, third-party reverse logistics providers' (3PRLP) selection problem is brought into consideration to manifest the sufficiency of the developed methodology. At the end of this study, we draw attention to a comparison between the proposed decision-making approach with the corresponding BCF-CRITIC-TOPSIS and BCF-CRITIC-WASPAS methods.