Optimization problem of (n+1) deliveries strategy for EPQ model with scrap in the supply chain environment

碩士 === 朝陽科技大學 === 工業工程與管理系碩士班 === 98 === This paper explores the optimal production quantity and optimal distribution strategies based on the (n+1) distribution model of imperfection production system. Generally, the cases in the inventory management course mainly focus on either perfect production...

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Bibliographic Details
Main Authors: Jne-Shun Lin, 林仁順
Other Authors: Yuan-Shyi Chiu
Format: Others
Language:zh-TW
Published: 2010
Online Access:http://ndltd.ncl.edu.tw/handle/52600803129075265844
Description
Summary:碩士 === 朝陽科技大學 === 工業工程與管理系碩士班 === 98 === This paper explores the optimal production quantity and optimal distribution strategies based on the (n+1) distribution model of imperfection production system. Generally, the cases in the inventory management course mainly focus on either perfect production or individual situation. However, the situations we take into account are very different from those actually happen in the real business field leading to defective items from the actual production. In addition, the production is not distributed together after the production process is completely finished. There are different production methods regarding different products. The distribution methods can vary while considering a variety of cost. Therefore, those cases we have studied can not provide us the actual picture of the production. This study applies different distribution method- manufacturers will conduct first distribution after spending t time for the production in order to satisfy customer’s need within t1. Next, we will apply quantitative method to conduct n distribution. Mathematical model structure is taken into account including promoting inventory cost to both manufacturers and customers. We expect to get the optimal production quantity and optimal number of distribution with the minimum inventory cost. Therefore, cost-effectiveness from the actual cases will be analyzed to provide more options in different business situations.