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IBM supply-chain network optimization workbench: an integrated optimization and simulation tool for supply chain design
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Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come table of contents
Washington D.C.
SESSION: Transportation and supply chain applications: simulation-based supply chain optimization table of contents
Pages 1940-1946  
Year of Publication: 2007
ISBN:1-4244-1306-0
Authors
Hongwei Ding  IBM China Research Laboratory, Haidian District, Beijing, P.R. China
Wei Wang  IBM China Research Laboratory, Haidian District, Beijing, P.R. China
Jin Dong  IBM China Research Laboratory, Haidian District, Beijing, P.R. China
Minmin Qiu  IBM China Research Laboratory, Haidian District, Beijing, P.R. China
Changrui Ren  IBM China Research Laboratory, Haidian District, Beijing, P.R. China
Sponsors
INFORMS-SIM : Institute for Operations Research and the Management Sciences: Simulation Society
NIST : National Institute of Standards and Technology
(SCS) : The Society for Modeling and Simulation International
ACM/SIGSIM : Association for Computing Machinery: Special Interest Group on Simulation
IIE : Institute of Industrial Engineers
ASA : American Statistical Association
IEEE/SMC : Institute of Electrical and Electronics Engineers: Systems, Man, and Cybernetics Society
Publisher
IEEE Press  Piscataway, NJ, USA
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ABSTRACT

The IBM Supply-chain Network Optimization Workbench (SNOW) is a software tool that can help a company make strategic business decisions about the design and operation of its supply chain network. The tool supports supply chain analysis with integrated network optimization and simulation capability. Mathematical programming models are used to first help identify some cost-effective scenarios from a large number of candidates. Optimization results are then converted to simulation models automatically for more detailed analysis with taking into account operational policies and uncertainties. The tool was applied to analyze both IBM's internal supply chains and external clients' supply chains. The combination of optimization and simulation demonstrates great value in real business cases.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Hongwei Ding: colleagues
Wei Wang: colleagues
Jin Dong: colleagues
Minmin Qiu: colleagues
Changrui Ren: colleagues