The selection of distribution center (DC) location is of paramount importance for production systems since an appropriate placement significantly influences transportation costs, delivery lead times, inventory management efficiency, and the overall level of customer service. Nevertheless, traditional MCDA methods in the prior literature fail to capture uncertainty, hesitancy, and vagueness of the subjective judgment. To overcome this challenge, this paper aims to apply the Pythagorean fuzzy TOPSIS (tchnique for order of preference by similarity to ideal solution) approach to select the most suitable location for the siting of a DC. The paper’s main originality is to integrate the traditional TOPSIS and the Pythagorean fuzzy sets (PFSs) to cope with uncertain information flexibly in the process of hesitant decision-making. The numerical example from the MBS Logistics & Warehousing Limited Group (hereafter MBS) demonstrates the Pythagorean fuzzy TOPSIS as a practical, flexible, and useful tool in dealing with uncertainty, hesitancy, and vagueness in practice. On top of that, sensitivity analysis with benchmarking and scenarios was carried out to assess the robustness of the proposed method in selecting a suitable location. The paper also provides theoretical references for methodological research in MCDM (multiple-criteria decision-making). In practice, DC managers can systematically compare different locations based on multiple factors (i.e., logistics system attractiveness, industrial hubs, transportation costs, etc.) while accounting for uncertainty in judgments.
Huynh et al. (Thu,) studied this question.