Location optimization of multiple distribution centers under fuzzy environment

Locating distribution centers optimally is a crucial and systematic task for decision-makers. Optimally located dis- tribution centers can significantly improve the logistics system＇s efficiency and reduce its operational costs. However, it is not an easy task to optimize distribution center locatio...

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Bibliographic Details
Published in:Journal of Zhejiang University. A. Science 2012-10, Vol.13 (10), p.782-798
Main Authors: Wang, Yong, Ma, Xiao-lei, Wang, Yin-hai, Mao, Hai-jun, Zhang, Yong
Format: Article
Language:English
Subjects:
Algorithms
Civil Engineering
Classical and Continuum Physics
Clustering
Criteria
Engineering
Fuzzy
Fuzzy logic
Fuzzy set theory
Industrial Chemistry/Chemical Engineering
Logistics
Mechanical Engineering
Optimization
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Summary:Locating distribution centers optimally is a crucial and systematic task for decision-makers. Optimally located dis- tribution centers can significantly improve the logistics system＇s efficiency and reduce its operational costs. 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 growing logistics demands, multiple distribution centers become necessary to meet customers＇ require- ments, but few studies have tackled the multiple distribution center locations （MDCLs） problem. This paper presents a compre- hensive algorithm to address the MDCLs 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 proposed approach developed in this study outperforms other similar algo- rithms for MDCLs selection. This new method may easily be extended to address location planning of other types of facilities, including hospitals, fire stations and schools.
ISSN:1673-565X
1862-1775
DOI:10.1631/jzus.A1200137