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A three-echelon supply chain with asymmetric information under uncertainty

  • Kai ZhuEmail author
  • Jiayu Shen
  • Xuelian Yao
Original Research

Abstract

This paper investigates a three-echelon supply chain problem in which multiple suppliers, a single manufacturer and a single retailer are participants. The manufacturer selects suppliers and estimates quantity of defective components purchased from the suppliers, but the quality information is unavailable for the manufacture due to asymmetric information. In addition, customers’ demands could not be predicated accurately either. Under this circumstance, quantity of defective components and demands of customers are all characterized as uncertain variables according to real trade. Based on uncertainty theory, three models under different criteria such as expected value criterion, chance-constrained one and measure-chance one are constructed for the problem and corresponding solution approach is proposed as well under uncertain environment. Finally, some numerical examples are given to show the applications of the problem.

Keywords

Supply chain Demand Asymmetric information Uncertain variables 

Notes

Funding

This study was funded by the Changzhou Application Basic Research Program (CJ20160050) and Natural science of Jiangsu Province (BK20170318).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

References

  1. Bag S (2013) A fuzzy supply chain model for defective items. Int J Eng Res Technol 2(12):3450–3468Google Scholar
  2. Chen X (2015) Uncertain calculus with finite variation processes. Soft Comput 19(10):2905–2912zbMATHGoogle Scholar
  3. Chen L, Peng J, Zhang B (2017) Uncertain goal programming models for bicriteria solid transportation problem. Appl Soft Comput 51:49–59Google Scholar
  4. Chen Z, Lan Y, Zhao R (2018) Impacts of risk attitude and outside option on compensation contracts under different information structures. Fuzzy Optim Decis Mak 17(1):13–47MathSciNetzbMATHGoogle Scholar
  5. Deng L, Zhu Y (2012) An uncertain optimal control model with n jumps and application. Comput Sci Inf Syst 9(4):1453–1468Google Scholar
  6. Devangan L, Amit R, Mehta P, Swami S, Shanker K (2013) Individually rational buyback contracts with inventory level dependent demand. Int J Prod Econ 142(2):381–387Google Scholar
  7. Esmaeili M, Zeephongsekul P (2010) Seller–buyer models of supply chain management with an asymmetric information structure. Int J Prod Econ 123(1):146–154Google Scholar
  8. Feng J, Lan Y, Zhao R (2017) Impact of price cap regulation on supply chain contracting between two monopolists. J Ind Manag Optim 13(1):347–371MathSciNetzbMATHGoogle Scholar
  9. Gao J, Yao K (2015) Some concepts and theorems of uncertain random process. Int J Intell Syst 30(1):52–65Google Scholar
  10. Gao R (2016) Milne method for solving uncertain differential equations. Appl Math Comput 274:774–785MathSciNetGoogle Scholar
  11. Hou J, Zeng A, Zhao L (2010) Coordination with a backup supplier through buy-back contract under supply disruption. Transp Res Part E Logist Transp Rev 46(6):881–895Google Scholar
  12. Kao C, Hsu W (2002) A single-period inventory model with fuzzy demand. Comput Math Appl 43(6–7):841–848MathSciNetzbMATHGoogle Scholar
  13. Ke H, Su T, Ni Y (2015) Uncertain random multilevel programming with application to product control problem. Soft Comput 19(6):1739–1746zbMATHGoogle Scholar
  14. Lau A, Lau H, Zhou Y (2007) A stochastic and asymmetric-information framework for a dominant-manufacturer supply chain. Eur J Oper Res 176(1):295–316zbMATHGoogle Scholar
  15. Lan Y, Zhao R, Tang W (2015) An inspection-based price rebate and effort contract model with incomplete information. Comput Ind Eng 83:264–272Google Scholar
  16. Lan Y, Liu Z, Niu B (2017) Pricing and design of after-sales service contract: the value of mining asymmetric sales cost information. Asia Pac J Oper Res 34(1):1740002MathSciNetzbMATHGoogle Scholar
  17. Lei D, Li J, Liu Z (2012) Supply chain contracts under demand and cost disruptions with asymmetric information. Int J Prod Econ 139(1):116–126Google Scholar
  18. Li L, Kabadi S, Nair K (2002) Fuzzy models for single-period inventory problem. Fuzzy Sets Syst 132(3):273–289MathSciNetzbMATHGoogle Scholar
  19. Li R, Liu G (2017) An uncertain goal programming model for machine scheduling problem. J Intell Manuf 28(3):689–694Google Scholar
  20. Liu B (2007) Uncertainty theory, 2nd edn. Springer, BerlinzbMATHGoogle Scholar
  21. Liu B (2009) Some research problems in uncertainty theory. J Uncertain Syst 3(1):3–10Google Scholar
  22. Liu B (2010) Uncertainty theory: a branch of mathematics for modeling human uncertainty. Springer, BerlinGoogle Scholar
  23. Liu B (2010) Uncertain risk analysis and uncertain reliability analysis. J Uncertain Syst 4(3):163–170Google Scholar
  24. Liu Y, Ralescu D (2017) Value-at-risk in uncertain random risk analysis. Inf Sci 391–392:1–8MathSciNetGoogle Scholar
  25. Shen J, Zhu Y (2016) Scheduling in a two-stage supply chain with uncertain parameters. J Intell Fuzzy Syst 30(6):3439–3449zbMATHGoogle Scholar
  26. Sheng L, Zhu Y, Hamalaonen T (2013) An uncertain optimal control with Hurwicz criterion. Appl Math Comput 224:412–421MathSciNetzbMATHGoogle Scholar
  27. Sheng Y, Gao J (2016) Exponential stability of uncertain differential equation. Soft Comput 20:3673–3678zbMATHGoogle Scholar
  28. Sun Y, Zhu Y (2017) Bang-bang property for an uncertain saddle point problem. J Intell Manuf 28(3):605–613Google Scholar
  29. Tse Y, Tan K (2012) Managing product quality risk and visibility in multi-layer supply chain. Int J Prod Econ 139(1):49–57Google Scholar
  30. Wang X, Lan Y, Tang W (2017) An uncertain wage contract model for risk-averse worker under bilateral moral hazard. J Ind Manag Optim 13(4):1815–1840MathSciNetzbMATHGoogle Scholar
  31. Yan H, Zhu Y (2015) Bang-bang control model for uncertain switched systems. Appl Math Model 39(10–11):2994–3002MathSciNetGoogle Scholar
  32. Yang X, Gao J, Kar S (2016) Uncertain calculus with Yao process. IEEE Trans Fuzzy Syst 24(6):1578–1585Google Scholar
  33. Yang K, Lan Y, Zhao R (2017) Monitoring mechanisms in new product development with risk-averse project manager. J Intell Manuf 28(3):667–681Google Scholar
  34. Yao K (2014) Multi-dimensional uncertain calculus with Liu process. J Uncertain Syst 8(4):244–254Google Scholar
  35. Yin S, Nishi T, Zhang G (2013) A game theoretic model to manufacturing planning with single manufacturer and multiple suppliers. Proced CIRP 7(12):115–120Google Scholar
  36. Zadeh L (1965) Fuzzy sets. Inf Control 8(3):338–353zbMATHGoogle Scholar
  37. Zhang X, Zeephongsekul P (2013) Asymmetric information supply chain models with credit option. Ind Eng Manag Syst 12(3):264–273Google Scholar
  38. Zhang C, Yu H, Huang X (2009) Quality control strategy in supply chain under asymmetric information. Int J Oper Res 4(1):97–116zbMATHGoogle Scholar
  39. Zhou Y (2007) A comparison of different quality discount pricing policies in a twoechelon channel with stochastic and asymmetric demand information. Int J Oper Res 181(2):686–703zbMATHGoogle Scholar
  40. Zhou C, Zhao R, Tang W (2008) Two-echelon supply chain games in a fuzzy environment. Comput Ind Eng 55(2):390–405Google Scholar
  41. Zhou J, Liu Y, Zhang X, Gu X, Wang D (2017) Uncertain risk aversion. J Intell Manuf 28(3):615–624Google Scholar
  42. Zhu Y (2012) Functions of uncertain variables and uncertain programming. J Uncertain Syst 6(4):278–288Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Automobile and Traffic EngineeringJiangsu University of TechnologyChangzhouChina
  2. 2.School of ScienceNanjing University of Science and TechnologyNanjingChina

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