Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 193, Issue 3, Pages 660-669Publisher
ELSEVIER
DOI: 10.1016/j.ejor.2007.06.055
Keywords
Inventory; Optimization; Anticipatory systems; Fuzzy sets; Decision support systems
Funding
- Ministry of Higher Education, Science and Technology of the Republic of Slovenia [UNI-MB-0586-P5-0018]
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The modern business environment is highly unpredictable. An anticipation approach in a real case study is presented to cope with such instability and minimize the total inventory cost without stock-outs occurring and inventory capacity being exceeded. The anticipation concept is performed using simulation models supported by inventory control algorithms on a selected sample of representative items. The inventory control algorithms include Silver-Meal, Part period balancing, Least-unit cost, and Fuzzy inventory control algorithm based on fuzzy stock-outs, highest inventory level and total cost. Transportation cost is explicitly defined as a discrete function of shipment size. The algorithms are tested on historic data. Simulation results are presented and the risk of accepting them as reliable is discussed. The process of simulation model implementation is briefly discussed to further validate the model and train order managers to use the simulation model in their order placement process. (C) 2007 Elsevier B.V. All rights reserved.
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