Efficient city supply chain management through spherical fuzzy dynamic multistage decision analysis

Abstract

The objective of this paper is to introduce several dynamic spherical fuzzy aggregation operators (AOs) for “multi-period decision-making” (MPDM) problems. In these problems, decision-makers (DMs) have access to all information in the form of spherical fuzzy numbers (SpFNs) that cover different time periods. AOs hold a crucial responsibility in the decision-making process, particularly in situations where there are conflicting factors that must be considered. When working with different data sets, the main problem is coming up with appropriate aggregating algorithms. “Spherical fuzzy dynamic Einstein weighted averaging (SpFDEWA) and spherical fuzzy dynamic Einstein weighted geometric (SpFDEWG) operators” are two novel Einstein AOs that we have introduced. These AOs have a number of enticing qualities that are discussed in detail. We also provide a method for dealing with MPDM issues using the best possible solutions. Along with an explanation of how the suggested method might be used, a numerical illustration of municipal supply chain management is given. A comparative analysis is conducted between the proposed and existing research to evaluate the efficacy of the proposed approach. An analysis of authenticity is also included to showcase the efficacy of the proposed strategy. Multi-stage and dynamic decision analysis are often pertinent to suggested pathways of action and decision-making processes in the real world.