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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:Yong-Tao Huang,Min Lv,Gang Wang,Bing-Yin Ren,Hao-Yun Zhang.Modeling and Analysis for Supply Chain Using Stochastic Process Algebra[J].Journal of Harbin Institute Of Technology(New Series),2014,21(6):74-80.DOI:10.11916/j.issn.1005-9113.2014.06.014.
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Modeling and Analysis for Supply Chain Using Stochastic Process Algebra
Author NameAffiliation
Yong-Tao Huang School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China 
Min Lv School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China 
Gang Wang School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China 
Bing-Yin Ren School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China 
Hao-Yun Zhang Henan Tongli Cement Co., Ltd., Zhengzhou 450000, China 
Abstract:
In order to improve the influence of the uncertain and dynamic of node enterprise behavior on the performance of supply chain, the method based on stochastic process algebra for description, analysis, validation and evaluation of supply chain business process model is proposed. Firstly, the description of the uncertainty of node enterprise behavior is given using the extended Unified Modeling Language sequence diagram, and mapping rule is defined from the extended Unified Modeling Language sequence diagram to stochastic process algebra. Secondly, on the basis of the acquired stochastic process algebra model, the supply chain business process model is verified with Mobility Workbench. Finally, according to the operational semantics of stochastic process algebra, the continuous-time Markov chain, isomorphic with stochastic process algebra model, is built; and the system performance evaluation of transient status and stable status is respectively conducted in accordance with Markov transfer relations and the current state of system, obtaining the predicted performance value and average performance index value for a specific period of time. The simulation experiments show that the proposed method can accurately describe the stochastic behaviors of supply chain system and interactions among nodes, effectively verify the validity of the model, and objectively and exactly evaluate design of the supply chain.
Key words:  supply chain  stochastic process algebra  business process  performance evaluation  Markov chain
DOI:10.11916/j.issn.1005-9113.2014.06.014
Clc Number:TP391.7
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