Optimizing Automotive LogisticsUsing MCGDM: A Data-Driven Approach to the Selection of Warehouse Location With Octagonal Neutrosophic Application

Abstract

Te domain of decision-making theory has made signifcant progress, especially within the industrial and management felds. Diverse decision-making challenges such as multicriteria decision-making (MCDM), multiattribute decision-making (MADM), and multiattribute group decision-making(MAGDM) have been thoroughly examined, equipping decision-makers with efective strategies for tackling these issues. In the context of the automotive industry, a specifc hurdle emerges when identifying the most suitable site for establishing a warehouse to store goods destined for multiple destinations. Tis article addresses a scenario amid uncertainty, leveraging substantial data. Neutrosophic sets (NSs) emerge as a comprehensive tool for efectively managing the imprecision inherent in such data. Among these sets, single-valued neutrosophic sets(SVNSs) stand out due to their adeptness in handling inconsistent or incomplete data. Te octagonal single-valued neutrosophic numbers (OSVNNs) has a new tool for representing the uncertainty information in a simplifed manner. Octagonal structure allows for representing diferent distinctions of truth, neutrality, and falsity of any complex situation and it is an efcient tool to compare diferent options based on their level of ambiguity. Tey have a wide range of applications in various felds, becoming increasingly important in addressing many difcult and uncertain issues. Te article aims to propose a new ranking function for OSVNNs to convert the OSVNN data into precise values, drawing from the existing mean interval method(MIM). Te conventional decision-making approaches such as weighted sum model(WSM), weighted product model(WPM), technique for order of preference by similarity to ideal solution (TOPSIS), and VlseKriterijumska Optimizacija I Kompromisno Resenje(VIKOR) are employed to obtain the optimal warehouse location using OSVN application. Furthermore, it demonstrates the application along with the proposed ranking function using the software MATLAB to determine the most favorable alternatives. Finally, sensitivity analyses are performed to assess how diferent scenarios could impact the optimal location selection for automotive logistics.