Fuzzy inference systems and inventory allocation decisions: Exploring the impact of priority rules on total costs and service levels

被引:19
作者
Wanke, Peter [1 ]
Alvarenga, Henrique [1 ]
Correa, Henrique [2 ]
Hadi-Vencheh, Abdollah [3 ]
Azad, Md. Abul Kalam [4 ]
机构
[1] Univ Fed Rio de Janeiro, COPPEAD Grad Business Sch, Rua Paschoal Lemme 355, BR-21949900 Rio De Janeiro, Brazil
[2] Rollins Coll, Crummer Grad Sch Business, 1000 Holt Ave 2722, Winter Pk, FL 32789 USA
[3] Islamic Azad Univ, Isfahan Khorasgan Branch, Dept Math, Esfahan, Iran
[4] Bangladesh Army Int Univ Sci & Technol, Sch Business, Dept Business Adm, Comilla 3501, Bangladesh
关键词
Inventory allocation; Fuzzy inference; Fuzzy systems; Inventory cost; Service level; STOCK ALLOCATION; ORDER QUANTITY; MONTE-CARLO; SET THEORY; DEMAND; MODELS; CHAIN; MANAGEMENT; BACKORDER; WAREHOUSE;
D O I
10.1016/j.eswa.2017.05.043
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Inventory allocation decisions in a distribution system concern issues such as how much and where stock should be assigned to orders in a supply chain. When the inventory level of an inventory point is lower than the total number of items ordered by lower echelons in the chain, the decision of how many items to allocate to each "competing" order must take into consideration the trade-off between cost and service level. This paper proposes a decision-support system that makes use of fuzzy logic to consider inventory carrying, shortage and ordering costs as well as transportation costs. The proposed system is compared through simulation with three other inventory allocation decision support models in terms of cost and service levels achieved. Conclusions are then drawn. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:182 / 193
页数:12
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