碩士 / 國立交通大學 / 運輸與物流管理學系 / 106 / When initially entering an emerging market, a company may export via local agents and sales subsidiary. After establishing its upstream suppliers and production factories, the company can further consider setting up its own distribution system in order to improve service level and increase profit. Based on the scenario, this study aims to optimize the location decision of distribution centers, given the fixed locations of the suppliers, plants, and retailers.
In particular, in this study, the upstream transportation operation is integrated; that is, supplier–plant and plant–distribution center are considered, with the objective of decreasing the number of empty backhauls. We also take the demand uncertainty into consideration to adapt to the changing business situations at the sites of retailers. We develop a mixed-integer programming (MIP) model based on the stochastic programming (SP) technique and a genetic algorithm to solve the location problem. Also, we use two indicators, namely Expected Value of Perfect Information (EVPI) and Value of Stochastic Solution (VSS), to evaluate the results of the stochastic programming model.
Based on the numerical experiments, it is found that we can decrease the total supply chain cost after considering upstream transportation integration and uncertain demand. Besides, the solution quality gap of the genetic algorithm with respect to the optimal solution is with less than 1% gap. In addition, more than 80% of the computational time can be saved.
| Identifer | oai:union.ndltd.org:TW/106NCTU5423039 |
| Date | January 2018 |
| Creators | Wu, Yu-Ching, 吳宇晴 |
| Contributors | Huang, Kuan-Cheng, 黃寬丞 |
| 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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