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Collaborative production planning of supply chain under price and demand uncertainty

Listed author(s):
  • Zhang, Guoquan
  • Shang, Jennifer
  • Li, Wenli
Registered author(s):

    This research is motivated by an automobile manufacturing supply chain network. It involves a multi-echelon production system with material supply, component fabrication, manufacturing, and final product distribution activities. We address the production planning issue by considering bill of materials and the trade-offs between inventories, production costs and customer service level. Due to its complexity, an integrated solution framework which combines scatter evolutionary algorithm, fuzzy programming and stochastic chance-constrained programming are combined to jointly take up the issue. We conduct a computational study to evaluate the model. Numerical results using the proposed algorithm confirm the advantage of the integrated planning approach. Compared with other solution methodologies, the supply chain profits from the proposed approach consistently outperform, in some cases up to 13% better. The impacts of uncertainty in demand, material price, and other parameters on the performance of the supply chain are studied through sensitivity analysis. We found the proposed model is effective in developing robust production plans under various market conditions.

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    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 215 (2011)
    Issue (Month): 3 (December)
    Pages: 590-603

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    Handle: RePEc:eee:ejores:v:215:y:2011:i:3:p:590-603
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    6. Naso, David & Surico, Michele & Turchiano, Biagio & Kaymak, Uzay, 2007. "Genetic algorithms for supply-chain scheduling: A case study in the distribution of ready-mixed concrete," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2069-2099, March.
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    10. Weng, Z. Kevin & McClurg, Tim, 2003. "Coordinated ordering decisions for short life cycle products with uncertainty in delivery time and demand," European Journal of Operational Research, Elsevier, vol. 151(1), pages 12-24, November.
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    12. Abdelaziz, Fouad Ben & Aouni, Belaid & Fayedh, Rimeh El, 2007. "Multi-objective stochastic programming for portfolio selection," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1811-1823, March.
    13. Leung, Stephen C.H. & Tsang, Sally O.S. & Ng, W.L. & Wu, Yue, 2007. "A robust optimization model for multi-site production planning problem in an uncertain environment," European Journal of Operational Research, Elsevier, vol. 181(1), pages 224-238, August.
    14. Burak Kazaz, 2004. "Production Planning Under Yield and Demand Uncertainty with Yield-Dependent Cost and Price," Manufacturing & Service Operations Management, INFORMS, vol. 6(3), pages 209-224, October.
    15. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
    16. AkartunalI, Kerem & Miller, Andrew J., 2009. "A heuristic approach for big bucket multi-level production planning problems," European Journal of Operational Research, Elsevier, vol. 193(2), pages 396-411, March.
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