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On flexible product-mix decision problems under randomness and fuzziness

  • Hasuike, Takashi
  • Ishii, Hiroaki
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    This paper considers several models of product-mix decision problems and production planning problems under uncertain conditions, and shows that these are extensional and versatile models for resolving previous product-mix problems. These proposed models include randomness derived from statistical analysis based on historical data, ambiguity of decision maker's intuition and the quality of received information, and flexibility in accomplishing the original plan. Furthermore, given that the upper limit values of some constraints have flexibility, and given a decision maker's level of satisfaction, we propose a flexible product mix of problems using the theory of constraints (TOC), and develop an efficient solution method. We then provide a numerical example that compares our models with some previous basic models. Efficiency of flexibility is obtained when our proposed models are applied to several conditions, such as measurable changes from the expected value of future returns.

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    Article provided by Elsevier in its journal Omega.

    Volume (Year): 37 (2009)
    Issue (Month): 4 (August)
    Pages: 770-787

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    Handle: RePEc:eee:jomega:v:37:y:2009:i:4:p:770-787
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    1. Wu, Jun & Li, Jian & Wang, Shouyang & Cheng, T.C.E., 2009. "Mean-variance analysis of the newsvendor model with stockout cost," Omega, Elsevier, vol. 37(3), pages 724-730, June.
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    7. Letmathe, Peter & Balakrishnan, Nagraj, 2005. "Environmental considerations on the optimal product mix," European Journal of Operational Research, Elsevier, vol. 167(2), pages 398-412, December.
    8. Olhager, Jan, 1993. "Manufacturing flexibility and profitability," International Journal of Production Economics, Elsevier, vol. 30(1), pages 67-78, July.
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    10. Bhattacharya, Arijit & Vasant, Pandian, 2007. "Soft-sensing of level of satisfaction in TOC product-mix decision heuristic using robust fuzzy-LP," European Journal of Operational Research, Elsevier, vol. 177(1), pages 55-70, February.
    11. Mula, J. & Poler, R. & Garcia-Sabater, J.P. & Lario, F.C., 2006. "Models for production planning under uncertainty: A review," International Journal of Production Economics, Elsevier, vol. 103(1), pages 271-285, September.
    12. Li, Jun & Xu, Jiuping, 2009. "A novel portfolio selection model in a hybrid uncertain environment," Omega, Elsevier, vol. 37(2), pages 439-449, April.
    13. Huang, Xiaoxia, 2007. "Two new models for portfolio selection with stochastic returns taking fuzzy information," European Journal of Operational Research, Elsevier, vol. 180(1), pages 396-405, July.
    14. Ding, Ding & Chen, Jian, 2008. "Coordinating a three level supply chain with flexible return policies," Omega, Elsevier, vol. 36(5), pages 865-876, October.
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