Personalized Individual Semantics-driven Group Consensus Decision-making Method with Linguistic Intuitionistic Fuzzy Information for the Evaluation of Third-party Logistics Service Providers

Abstract

The rapid development of e-commerce often delegates logistical tasks to third-party logistics (3PLs) service providers to acquire a competitive edge in the dynamic market. But, selecting the most suitable 3PL partner is a multifaceted task that requires careful evaluation of various criteria and alternatives. In response to this issue, numerous multi-criteria decision-making (MCDM) methods have been developed, each aiming to enhance group decision-making in complex scenarios involving multiple criteria. However, challenges persist, particularly in measuring and integrating intuitionistic evaluations, as well as addressing issues related to weighting. Accordingly, this paper innovatively develops a personalized individual semantics (PISs)-driven group consensus decision-making method for 3PLs service providers selection. Specifically, a Hamming distance formula for linguistic intuitionistic fuzzy numbers (LIFNs) is developed considering the PISs of decision-makers (DMs). Furthermore, a consensus-driven optimization model for improving the consensus level is constructed. Finally, the decision-making process is conducted with the evaluation of 3PLs service providers. The proposed method focuses on checking and improving consensus reaching processes, it avoids the processes of consistency checking and improving in the pairwise judgment matrix, and more suitable for decision-making problems in some backgrounds. The proposed method provides a technical path for relevant departments to make decisions on practical issues.

Keywords

Contract logistics provider / group decision-making / linguistic intuitionistic information / consensus model / personalized semantics

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