Optimizing beer distribution game order policy using numerical simulations
Name
587497475-MIT.pdf
Description
Full printable version
Size
4.92 MB
Format
Adobe PDF
Checksum (MD5)
1baf32143cdbf329ff9c7669805d2c2b
Author(s)
Xiao, Qinwen
Advisor(s)
James B. Orlin and David Simchi-Levi.
Date Issued
2009
Publisher
Massachusetts Institute of Technology
Abstract
One of the major challenges in supply chain management is the level of information availability. It is very hard yet important to coordinate each stage in the supply chain when the information is not centralized and the demand is uncertain. In this thesis, I analyzed the bullwhip effect in supply chain management using the MIT Beer Distribution Game. I also proposed heuristics and models to optimize the MIT Beer Distribution Game order policy when the customer's demand is both known and unknown. The proposed model provides each player with an order policy based on how many weeks of inventory the player needs to keep ahead to minimize the global cost of the supply chain. The optimized order policy is robust, practical, and generated by numerical simulations. The model is applied in a number of experiments involving deterministic and random demand and lead time. The simulation results of my work are compared with two other artificial agent algorithms, and the improvements brought by my results are presented and analyzed.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2009.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 63-64).
Subjects
Computation for Design and Optimization Program.
MIT Department
Massachusetts Institute of Technology. Computation for Design and Optimization Program
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