Intelligent Logistics Supplier Selection Based On Improved Agglomerative Hierarchical Clustering Algorithm - ZHANG, Yajie; LV, Yaqiong; TU, Lei; HOU, Yueqiu (IEEE International Conference on Industrial Informatics (INDIN), 2019)
Most enterprises concentrate on their own core industries and cannot independently complete non-core business logistics activities. One way to solve this problem is logistics outsourcing. Therefore, how to select suitable logistics suppliers has become the key to meet the logistics needs of enterprises. Combining with the existing supplier selection index system and the logistics demand of enterprises, this paper chooses four aspects which can reflect the comprehensive strength of suppliers according to the theoretical basis of selecting third-party logistics suppliers. This paper subdivides these four aspects, summarizes 10 evaluation indicators of supplier selection, and establishes a relatively scientific and reasonable index system. Then, the weight of each index is determined by analytic hierarchy process. For supplier processing, clustering analysis is used to classify supplier types. By comparing and analyzing the advantages and disadvantages of three common-used clustering methods, this paper proposed an improved hierarchical clustering method, which can effectively determine the cluster center coordinates and improve the accuracy of supplier classification. Finally, a comprehensive evaluation method of third-party logistics suppliers is established by combining the weights determined by the analytic hierarchy process with the clustering results.