Optimized (r,Q) Inventory Model under Diverse Customer Service Level Control

碩士 === 逢甲大學 === 工業工程與系統管理學研究所 === 94 === The major goal of the inventory management is to keep the cost under a reasonable boundary and also keep the customer requirement satisfied. In order to reach this goal, the decision maker has to minimize the stock as well as fulfill the customer service leve...

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Bibliographic Details
Main Authors: Hung-Jui Pai, 白鴻叡
Other Authors: Ming-Shiun Lu
Format: Others
Language:zh-TW
Published: 2006
Online Access:http://ndltd.ncl.edu.tw/handle/77962500222472442516
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Summary:碩士 === 逢甲大學 === 工業工程與系統管理學研究所 === 94 === The major goal of the inventory management is to keep the cost under a reasonable boundary and also keep the customer requirement satisfied. In order to reach this goal, the decision maker has to minimize the stock as well as fulfill the customer service level. Consequently, the model of inventory management has to consider two factors: 1.)customer service level; 2.) lowest cost of ordering, holding and shortages. A three-echelon inventory system consisting of supplier, retailer and downstream customers will be developed in this research. In this system, retailer is required to satisfy the demand of service level β and to determine reorder point r and ordering quantity Q which would lead to minimized inventory cost. After the inventory model is built, an algorithm for acquiring the reorder point r and ordering quantity Q which lead to the lowest total cost under the required service level will also be developed. Thereafter any decision maker in an enterprise will be able to make out an optimal reorder point r and ordering quantity Q when facing a thirsty demand and a trict level of customer service. In developing the algorithm, the values of parameter, average demands for a cycle and standard deviations will be considered in the rule of algorithm. Finally the sensitivity analysis will be performed to see how the ordering cost, holding cost, and shortage cost affect the total cost through the total cost curve. This analysis will help to determine the decision parameters.