Analysis and Recognition for Industry Characteristics of Emergency in Supply Chain Based on Fuzzy Clustering

Author

Xu Lei ; Dong Qianli ; Liu Kaizheng

Author_Institution

Sch. of Econ. & Manage., Chang´an Univ., Xi´an, China

Volume

1

fYear

2010

fDate

7-8 Aug. 2010

Firstpage

430

Lastpage

432

Abstract

To find the industry characteristics of emergency in supply chain and to solve the problem of recognition about that. The paper established causation factor indexes system of emergency in supply chain based on systems analytical method, and at the same time, put forward a industry characteristics recognition model for emergency supply chain based on fuzzy clustering utilizing fuzzy similarity relation, fuzzy equivalence relation and fuzzy equivalence matrix. An empirical analysis is carried out to find the characteristics of IT, chemical, auto, transportation and other 6 industries under supply chain emergency, which indicates that IT, medicine and chemical, transportation, agriculture, steel have similar characteristics of supply chain emergency respectively, and the established model is applicable for solving the problem.

Keywords

emergency services; fuzzy set theory; matrix algebra; pattern clustering; production engineering computing; supply chain management; causation factor indexes system; emergency supply chain; fuzzy clustering; fuzzy equivalence matrix; fuzzy equivalence relation; fuzzy similarity relation; industry characteristic recognition; industry characteristic recognition model; system analytical method; Analytical models; Character recognition; Chemicals; Indexes; Industries; Materials; Supply chains; characteristics recognition; emergency in supply chain; fuzzy clustering; logistics engineering and management;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science and Management Engineering (ISME), 2010 International Conference of

Conference_Location

Xi´an

Print_ISBN

978-1-4244-7669-5

Electronic_ISBN

978-1-4244-7670-1

Type

conf

DOI

10.1109/ISME.2010.249

Filename

5572034