碩士 / 國立交通大學 / 工業工程與管理系所 / 93 / This thesis proposes an approach to reduce the operating cost of a spare part supply chain system. Such a supply chain system is a network consisting of many nodes. The reduction of transportation time between any two nodes may reduce the inventory level of each node; at the price of paying more transportation fees. This research aims to identify an optimal transportation configuration. The proposed approach involves four major stages. First, we use OPUS10, a commercial software for effectively designing a spare part supply chain system, as a tool for computing the inventory levels for some sampled supply chain transportation configurations. Second, a neural network approach is used to establish a fast-computing mechanism to emulate the function of OPUS10. Third, a genetic algorithm is developed to identify a near optimal transportation configuration. Finally, a simulation program is developed to accurately evaluate the performance of the identified transportation configuration.
| Identifer | oai:union.ndltd.org:TW/093NCTU5031018 |
| Date | January 2005 |
| Creators | Ya-Jiuan Lin, 林雅娟 |
| Contributors | Muh-Cherng Wu, 巫木誠 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 41 |
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