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Journal of Optimization
Volume 2013 (2013), Article ID 197370, 14 pages
http://dx.doi.org/10.1155/2013/197370
Research Article

An Optimal Method for Developing Global Supply Chain Management System

1Department of Information Management, College of Management, Fu Jen Catholic University, No.510 Jhongjheng Road, Sinjhuang City, Taipei County 242, Taiwan
2Institute of Information Management, National Chiao Tung University, Management Building 2, 1001 Ta-Hsueh Road, Hsinchu 300, Taiwan

Received 31 January 2013; Accepted 2 June 2013

Academic Editor: Irem Ozkarahan

Copyright © 2013 Hao-Chun Lu and Yao-Huei Huang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. D. J. Thomas and P. M. Griffin, “Coordinated supply chain management,” European Journal of Operational Research, vol. 94, no. 1, pp. 1–15, 1996. View at Publisher · View at Google Scholar · View at Scopus
  2. S. C. Graves and S. P. Willems, “Optimizing the supply chain configuration for new products,” Management Science, vol. 51, no. 8, pp. 1165–1180, 2005. View at Publisher · View at Google Scholar · View at Scopus
  3. H. L. Lee and J. Rosenblatt, “A generalized quantity discount pricing model to increase supplier’s profits,” Management Science, vol. 33, no. 9, pp. 1167–1185, 1986. View at Google Scholar
  4. J. P. Monahan, “A quantity pricing model to increase vendor profits,” Management Science, vol. 30, no. 6, pp. 720–726, 1984. View at Google Scholar · View at Scopus
  5. C. Hofmann, “Supplier's pricing policy in a just-in-time environment,” Computers and Operations Research, vol. 27, no. 14, pp. 1357–1373, 2000. View at Publisher · View at Google Scholar · View at Scopus
  6. P. C. Yang, “Pricing strategy for deteriorating items using quantity discount when demand is price sensitive,” European Journal of Operational Research, vol. 157, no. 2, pp. 389–397, 2004. View at Publisher · View at Google Scholar · View at Scopus
  7. J.-F. Tsai, “An optimization approach for supply chain management models with quantity discount policy,” European Journal of Operational Research, vol. 177, no. 2, pp. 982–994, 2007. View at Publisher · View at Google Scholar · View at Scopus
  8. B. L. Foote, “On the implementation of a control-based forecasting system for aircraft spare parts procurement,” IIE Transactions, vol. 27, no. 2, pp. 210–216, 1995. View at Google Scholar · View at Scopus
  9. A. A. Ghobbar and C. H. Friend, “Evaluation of forecasting methods for intermittent parts demand in the field of aviation: a predictive model,” Computers and Operations Research, vol. 30, no. 14, pp. 2097–2114, 2003. View at Publisher · View at Google Scholar · View at Scopus
  10. F.-L. Chu, “Forecasting tourism demand: a cubic polynomial approach,” Tourism Management, vol. 25, no. 2, pp. 209–218, 2004. View at Publisher · View at Google Scholar · View at Scopus
  11. X. Zhao, J. Xie, and J. Leung, “The impact of forecasting model selection on the value of information sharing in a supply chain,” European Journal of Operational Research, vol. 142, no. 2, pp. 321–344, 2002. View at Publisher · View at Google Scholar · View at Scopus
  12. H. L. Lee, V. Padmanabhan, and S. Whang, “The bullwhip effect in supply chains,” Sloan Management Review, vol. 38, no. 3, pp. 93–102, 1997. View at Google Scholar · View at Scopus
  13. F. Chen, Z. Drezner, J. K. Ryan, and D. Simchi-Levi, “Quantifying the bullwhip effect in a simple supply chain: the impact of forecasting, lead times, and information,” Management Science, vol. 46, no. 3, pp. 436–443, 2000. View at Google Scholar · View at Scopus
  14. R. J. Kuo, “Sales forecasting system based on fuzzy neural network with initial weights generated by genetic algorithm,” European Journal of Operational Research, vol. 129, no. 3, pp. 496–517, 2001. View at Publisher · View at Google Scholar · View at Scopus
  15. F. B. Gorucu, P. U. Geriş, and F. Gumrah, “Artificial neural network modeling for forecasting gas consumption,” Energy Sources, vol. 26, no. 3, pp. 299–307, 2004. View at Publisher · View at Google Scholar · View at Scopus
  16. H. C. Chen, H. M. Wee, and Y. H. Hsieh, “Optimal supply chain inventory decision using artificial neural network,” in Proceedings of the WRI Global Congress on Intelligent Systems (GCIS '09), pp. 130–134, May 2009. View at Publisher · View at Google Scholar · View at Scopus
  17. B. Bilgen, “Application of fuzzy mathematical programming approach to the production allocation and distribution supply chain network problem,” Expert Systems with Applications, vol. 37, no. 6, pp. 4488–4495, 2010. View at Publisher · View at Google Scholar · View at Scopus
  18. C. R. Moberg, B. D. Cutler, A. Gross, and T. W. Speh, “Identifying antecedents of information exchange within supply chains,” International Journal of Physical Distribution and Logistics Management, vol. 32, no. 9, pp. 755–770, 2002. View at Google Scholar
  19. S. Li and B. Lin, “Accessing information sharing and information quality in supply chain management,” Decision Support Systems, vol. 42, no. 3, pp. 1641–1656, 2006. View at Publisher · View at Google Scholar · View at Scopus
  20. F.-R. Lin, S.-H. Huang, and S.-C. Lin, “Effects of information sharing on supply chain performance in electronic commerce,” IEEE Transactions on Engineering Management, vol. 49, no. 3, pp. 258–268, 2002. View at Publisher · View at Google Scholar · View at Scopus
  21. G. P. Cachon and M. Fisher, “Supply chain inventory management and the value of shared information,” Management Science, vol. 46, no. 8, pp. 1032–1048, 2000. View at Google Scholar · View at Scopus
  22. C.-C. Huang and S.-H. Lin, “Sharing knowledge in a supply chain using the semantic web,” Expert Systems with Applications, vol. 37, no. 4, pp. 3145–3161, 2010. View at Publisher · View at Google Scholar · View at Scopus
  23. M.-M. Yu, S.-C. Ting, and M.-C. Chen, “Evaluating the cross-efficiency of information sharing in supply chains,” Expert Systems with Applications, vol. 37, no. 4, pp. 2891–2897, 2010. View at Publisher · View at Google Scholar · View at Scopus
  24. D. Trefler, “Trade liberalization and the theory of endogenous protection: an econometric study of US import policy,” Journal of Political Economy, vol. 101, no. 1, pp. 138–160, 1993. View at Publisher · View at Google Scholar · View at Scopus
  25. M. S. Iman and A. Nagata, “Liberalization policy over foreign direct investment and the promotion of local firms development in Indonesia,” Technology in Society, vol. 27, no. 3, pp. 399–411, 2005. View at Publisher · View at Google Scholar · View at Scopus
  26. B. Romagnoli, V. Menna, N. Gruppioni, and C. Bergamini, “Aflatoxins in spices, aromatic herbs, herb-teas and medicinal plants marketed in Italy,” Food Control, vol. 18, no. 6, pp. 697–701, 2007. View at Publisher · View at Google Scholar · View at Scopus
  27. R. D. C. Israel, “A comparative welfare analysis of the duty drawback and the common bonded warehouse schemes,” Philippine Review of Economics, vol. 30, no. 2, 1993. View at Google Scholar
  28. B. Yang, “Political democratization, economic liberalization, and growth volatility,” Journal of Comparative Economics, vol. 39, no. 2, pp. 245–259, 2011. View at Publisher · View at Google Scholar · View at Scopus
  29. C.-S. Yu and H.-L. Li, “Robust optimization model for stochastic logistic problems,” International Journal of Production Economics, vol. 64, no. 1, pp. 385–397, 2000. View at Publisher · View at Google Scholar · View at Scopus
  30. LINGO, Release. 8, Lindo System, Chicago, Ill, USA, 2002.
  31. H. Kantz, T. Schreiber, and R. S. Mackay, Nonlinear Time Series Analysis, Cambridge University Press, Cambridge, UK, 1997.
  32. T. Schreiber, “Interdisciplinary application of nonlinear time series methods,” Physics Report, vol. 308, no. 1, pp. 1–64, 1999. View at Google Scholar · View at Scopus
  33. H. L. Li, Supply Chain Management and Decision Making, Nonlinear Models of Supply Chain, chapter 4, 2004.
  34. D. A. Babayev, “Piece-wise linear approximation of functions of two variables,” Journal of Heuristics, vol. 2, no. 4, pp. 313–320, 1997. View at Google Scholar · View at Scopus