Analysis of inventory level under procurement constraints in supply chain

被引:0
作者
Chang Guangshu [1 ]
机构
[1] Zhengzhou Inst Aeronaut, Zhengzhou 450015, Henan, Peoples R China
基金
美国国家科学基金会;
关键词
supply chain; inventory management; (s; S); strategy;
D O I
10.1007/s11465-007-0063-1
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Because the inventory is one of the major factors that affect the performance of the supply chain system, efficient reduction of an inventory can effectively reduce the cost level of the total supply chain. Therefore, inventory management is an important means to optimize the operation of a supply chain and enhance the competitive advantage. Considering the (s, S) policy in an inventory management, this paper establishes a model of the inventory level. Then, the change of the inventory level with and without the procurement constraints is analyzed, and their expectation and variance calculated. Consequently, the order point can be determined accurately to reduce the inventory level and the operation risk.
引用
收藏
页码:361 / 363
页数:3
相关论文
共 12 条
[1]  
Cao W B, 2000, CHINESE J MANAGEMENT, V8, P768
[2]   Sensitivity analysis of an (s,S) inventory model [J].
Chen, FR ;
Zheng, YS .
OPERATIONS RESEARCH LETTERS, 1997, 21 (01) :19-23
[3]  
CHEN RQ, 2004, PRODUCTION OPERATION
[4]   Inventory models with random yield in a random environment [J].
Erdem, AS ;
Özekici, S .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2002, 78 (03) :239-253
[5]   Managing demand uncertainty in supply chain planning [J].
Gupta, A ;
Maranas, CD .
COMPUTERS & CHEMICAL ENGINEERING, 2003, 27 (8-9) :1219-1227
[6]  
Kruger GA, 1997, HEWLETT-PACKARD J, V48, P28
[7]   Multiple-supplier inventory models in supply chain management: A review [J].
Minner, S .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2003, 81-2 :265-279
[8]  
NAHMIAS S, 1993, PRODUCTION OPERATION
[9]   Mixture inventory model involving variable lead time with a service level constraint [J].
Ouyang, LY ;
Wu, KS .
COMPUTERS & OPERATIONS RESEARCH, 1997, 24 (09) :875-882
[10]  
Ross SM, 1996, STOCHASTIC PROCESS