The Effects of Information Sharing in a Two-stage Apparel Supply Chain Using Policy Characterization and Simulation
dc.contributor.advisor | Jeffrey Joines, Committee Co-Chair | en_US |
dc.contributor.advisor | Kristin Thoney-Barletta, Committee Chair | en_US |
dc.contributor.author | Yoon, Seonghoo | en_US |
dc.date.accessioned | 2010-04-02T19:02:01Z | |
dc.date.available | 2010-04-02T19:02:01Z | |
dc.date.issued | 2007-12-18 | en_US |
dc.degree.discipline | Textile Technology Management | en_US |
dc.degree.level | dissertation | en_US |
dc.degree.name | PhD | en_US |
dc.description.abstract | The purpose of this research is to characterize the inventory policies of a two-stage apparel supply chain, consisting of an apparel producer and a retail store, based on the optimal policies obtained by a Markov Decision Process (MDP) and to test the characterized policies on seasonal demand patterns using simulation. First, the optimal policies for the apparel producer and the retail store were obtained using the MDP experiments. Based on these results, characterized policies for the apparel producer and the retail store were obtained by comparing the MDP results to standard policies such as (Q, r), (s, S), and echelon stock policies. The characterized policies were found to be either optimal or near-optimal. By using the policy characterized for the changes in cost, the total gain of the supply chain was increased compared to using the base policy for that problem. A neural network model found the characterized policies for the apparel producer and the retail store when multiple numbers of costs were changed. The neural network models also obtained near-optimal policies for the models used in this research. Then, the two-stage apparel supply chain with different types of seasonal demands was simulated. Since the apparel producer and the retail store's inventory policies were highly correlated to the mean and coefficient of variation (CV) of demand, corresponding policies were required to be changed when the demand had a seasonal pattern in order to increase the total gain of the supply chain. Different options were compared to find the optimal week to change the policy. Option B, which changed policies one week prior to the increase in the mean of demand and changed policies in the same week that the mean of demand decreases, produced the highest gains for both the no information sharing model and the information sharing model. The simulation results showed that by sharing the retail store's inventory information, both the apparel producer and the retail store could increase their gains. Moreover, the retail store's gain was increased by a higher percentage than the apparel producer. | en_US |
dc.identifier.other | etd-12132007-095121 | en_US |
dc.identifier.uri | http://www.lib.ncsu.edu/resolver/1840.16/4848 | |
dc.rights | I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dis sertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. | en_US |
dc.subject | Information sharing | en_US |
dc.subject | supply chain management | en_US |
dc.subject | characterization | en_US |
dc.subject | simulation | en_US |
dc.subject | apparel supply chain | en_US |
dc.title | The Effects of Information Sharing in a Two-stage Apparel Supply Chain Using Policy Characterization and Simulation | en_US |
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