Extended VIKOR Method based on Interval-Valued Intuitionistic Fuzzy Numbers for Selection of Logistics Centre Location

Abstract

Identifying the appropriate location for logistics centres (LC) is key to gaining and maintaining a competitive advantage and increasing the efficiency of supply chain activities. Increasing customer expectations, efforts to reduce logistics costs and the intensity of competition in the logistics sector have led to the establishment of many new LMs in recent years. These centers contribute significantly to increasing efficiency in freight transportation, optimizing logistics services and reducing the traffic. The increasing importance of LCs and the significant impact of their location on logistics activities have made the choice of installation site a strategic consideration. However, evaluating LC location alternatives is a complex process that must take many factors into account. The aim of the present study is to propose an extended VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) approach based on interval-valued intuitionistic fuzzy numbers (IVIFN) and test its feasibility. Applying IVIFN contributes to coping with uncertainty in human thought and decision processes. On the other hand, VIKOR is a decision-making technique that facilitates ranking criteria that are contradictory and represented by different units, and it offers a compromise solution. The feasibility of the extended VIKOR approach through IVIFN proposed in this study was tested in a numerical example in which LC location alternatives were evaluated. Three experts were consulted to determine the criterion weights and to rank the alternatives. Decision makers serve as logistics and planning specialist, logistics operations manager and supply chain chief engineer. In practice, alternatives were evaluated by considering six criteria. As a result, criteria are listed in the form of intermodal connection (0.255), infrastructure (0.194), security/safety (0.169), proximity to customers (0.158), proximity to suppliers (0.131), and labour supply (0.093), according to their weighted importance. It is expected that the findings obtained in the study will contribute to researchers and sector managers.