Abstract
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.
Highlights
To begin with reverse logistics (RLs), it is uniformly essential to distinguish what RL is and how it functions
In “BCF-CRITIC-MULTIMOORA methodology for decision-making”, we develop a novel BCF-CRITIC-MULTIMOORA framework with CRITIC method and the proposed aggregation operators (AOs) where the criteria values take the form of bipolar complex fuzzy number (BCFN)
We know that uncertainty is one of the widespread and major problems arising in the procedure of multi-criteria decision-making (MCDM) because of time-bound, a dearth of information, or larger complexity of socioeconomic conditions
Summary
To begin with reverse logistics (RLs), it is uniformly essential to distinguish what RL is and how it functions. RLs turn into an inexorable policy for production-based industries in the modern period [1]. Far, using this policy requires a skilled support panel, in addition, formation of both design and plan of a robust network together with mending and charging professionals for keeping the network operational, owing to the complications associated with RLs performance [88, 99]. Several companies engaged themselves in outsourcing these logistics functions into learned third-party reverse logistics providers (3PRLPs) that in turn effectively reducing price and upraise the efficiency of regaining of second-hand products that are already dispatched for creating competition towards the advantages [34, 74]. The criteria involved in this process may fluctuate based on the type of considered item and often conflict with each other [59]
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