Scheduling Performance Evaluation of Logistics Service Supply Chain Based on the Dynamic Index Weight
Author(s) -
Weihua Liu,
Zhicheng Liang,
Shuqing Wang,
Liu Yang,
Wenchen Xie
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/280741
Subject(s) - scheduling (production processes) , computer science , supply chain , dynamic priority scheduling , service level , reliability engineering , operations research , quality of service , mathematical optimization , engineering , mathematics , statistics , computer network , political science , law
Scheduling is crucial to the operation of logistics service supply chain (LSSC), so scientific performance evaluation method is required to evaluate the scheduling performance. Different from general project performance evaluation, scheduling activities are usually continuous and multiperiod. Therefore, the weight of scheduling performance evaluation index is not unchanged, but dynamically varied. In this paper, the factors that influence the scheduling performance are analyzed in three levels which are strategic environment, operating process, and scheduling results. Based on these three levels, the scheduling performance evaluation index system of LSSC is established. In all, a new performance evaluation method proposed based on dynamic index weight will have three innovation points. Firstly, a multiphase dynamic interaction method is introduced to improve the quality of quantification. Secondly, due to the large quantity of second-level indexes and the requirements of dynamic weight adjustment, the maximum attribute deviation method is introduced to determine weight of second-level indexes, which can remove the uncertainty of subjective factors. Thirdly, an adjustment coefficient method based on set-valued statistics is introduced to determine the first-level indexes weight. In the end, an application example from a logistics company in China is given to illustrate the effectiveness of the proposed method.
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