Mixture inventory models involving fuzzy annual demand and fuzzy backorder rate

• Main Authors: Ke-Chun Chen, 陳克群
• Other Authors: Jason Chao-Hsien Pan
• Format: Others
• Language: en_US
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/39225926941009426943

碩士 === 國立臺灣科技大學 === 工業管理系 === 93 === In today’s competitive marketplace, companies have to earn and maintain the advantages themselves. Through the production management, companies can effectively reduce their cost and raise competition. However, the inventory problem plays a more important role in production management then before. Therefore, how to efficiently control the inventory level becomes a very important issue. This paper investigates the backorder rate inventory problem with variable lead time. In this paper, the variable lead time can be decomposed into several components, each having a crashing cost function for the respective reduced lead time. The objective is to find the optimal order quantity and the lead time simultaneously, and then minimizing the total inventory cost. In the past, most of the published data assumes that the annual demand is deterministic and the backorder rate is in proportion to the price discount offered by the supplier. However, there are many uncertain factors in practical situations. Therefore, they can be described by fuzzy sense. Here, we use the concept of fuzziness to joint the mixture inventory system, and construct the solution procedure to find the optimal order quantity and lead time. For each model, we utilize the signed distance, a ranking method for fuzzy numbers, to find the estimate of annual demand and backorder rate in the fuzzy sense, and then derive the corresponding optimal solution. Numerical examples are included to illustrate the procedures of the solution.