Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/154060
DC Field | Value | |
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dc.title | INVENTORY MANAGEMENT FOR MARGIN MANAGEMENT SYSTEM | |
dc.contributor.author | SUN ZHIBO | |
dc.date.accessioned | 2019-05-13T07:56:36Z | |
dc.date.available | 2019-05-13T07:56:36Z | |
dc.date.issued | 2010 | |
dc.identifier.citation | SUN ZHIBO (2010). INVENTORY MANAGEMENT FOR MARGIN MANAGEMENT SYSTEM. ScholarBank@NUS Repository. | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/154060 | |
dc.description.abstract | We examine various inventory management models and identify a best practice for Acceval™s Margin Management System. With simulated annealing and binary search, we develop two effective and efficient algorithms to solve the dynamic programming procedure of a single product, periodic review, finite horizon model and compute the optimal policy under both stochastic additive demand and stochastic multiplicative demand. We also formulate an alternative fixed price policy and compare it with the policy to investigate their empirical performances. After discussing the limitations of the model, we propose two possible improvements for implementing the model as a prototype of the supply chain optimization model for Acceval™s Margin Management System. | |
dc.source | SMA BATCHLOAD 20190422 | |
dc.subject | Inventory Management | |
dc.subject | Supply Chain Pricing | |
dc.subject | Dynamic Programming | |
dc.subject | Simulated Annealing | |
dc.subject | K-convexity | |
dc.type | Thesis | |
dc.contributor.department | SINGAPORE-MIT ALLIANCE | |
dc.contributor.supervisor | CHUNG CHEE KONG | |
dc.contributor.supervisor | WANG JIAN-SHENG | |
dc.description.degree | Master's | |
dc.description.degreeconferred | MASTER OF SCIENCE IN COMPUTATIONAL ENGINEERING | |
dc.description.other | Dissertation Supervisors: 1. Mr. Chung Chee Kong, Managing Director, Acceval. 2. Prof. Wang Jian-Sheng, SMA Fellow, NUS | |
Appears in Collections: | Master's Theses (Restricted) |
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Sun Zhibo_CE Master Thesis_Sun Zhibo.pdf | 757.24 kB | Adobe PDF | RESTRICTED | None | Log In |
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