Selecting an appropriate warehouse location is crucial for optimizing logistics costs and enhancing service quality, which requires evaluating multiple conflicting criteria. This study proposes a hybrid approach that combines the fuzzy best worst method (FBWM) and the technique for order preference by similarity to ideal solution (TOPSIS) to determine the optimal warehouse location. FBWM is applied to derive criteria weights under expert uncertainty, while TOPSIS ranks the alternatives. A case study with three warehouse options evaluated based on area, rental rate, and distance to the airport demonstrates the method’s effectiveness. To assess robustness, closeness coefficients are evaluated under four configurations, combining two normalization techniques (Linear vector, Linear sum) with two distance metrics (Euclidean, Manhattan). Results show a slight variation in values across configurations but consistent rankings, indicating the method’s stability. The findings highlight the practical value and adaptability of the proposed FBWM-TOPSIS framework for multi-criteria warehouse location decisions.