Location Optimization of Multiple Distribution Centers under Fuzzy Environment

Locating distribution centers optimally is a crucial and systematic task for logistic operators and decision makers. Optimally located distribution centers can significantly improve the logistic system’s efficiency and reduce its operational cost. However, it is not an easy task to optimize distribution center locations and previous studies focused primarily on location optimization of a single distribution center. With the growing logistics demands, multiple distribution centers become necessary to meet customers’ requirements, but few studies have tackled the Multiple Distribution Centers Location (MDCL) problems. This paper presents a comprehensive algorithm to address the MDCL problem. Fuzzy integration and clustering approach using the Improved Axiomatic Fuzzy Set (AFS) theory is developed for location clustering based on multiple hierarchical evaluation criteria. Then, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied for evaluating and selecting the best candidate for each cluster. Sensitivity analysis is also conducted to assess the influence of each criterion in the location planning decision procedure. Results from a case study in Guiyang, China, reveals that the approach developed in this study outperforms other similar algorithms for multiple distribution center location selections. This new method may easily be extended to address location planning of other types of facilities, including hospitals, fire stations, and schools.