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Discrete Switched Model and Fuzzy Robust Control of Dynamic Supply Chain Network

Author

Listed:
  • Songtao Zhang
  • Chunyang Zhang
  • Siqi Zhang
  • Min Zhang

Abstract

Supply chain network is more complex and dynamic under the uncertain demand and the lead time. Robustness is a key index of the stable operation for the supply chain network. We investigate a fuzzy robust strategy to realize the robust operation of the supply chain network with the production lead times and the ordering lead times under the uncertain customer demand. A discrete switched model of the dynamic supply chain network with the lead times and the uncertain customer demand is established based on T-S fuzzy systems. Then a fuzzy switched strategy is proposed to control the switching actions among subsystems. Furthermore, by introducing the inhibition rate , a fuzzy control strategy for the dynamic supply chain network is put forward to suppress the impacts of the lead times and the uncertain customer demand on the operation of the dynamic supply chain network. The fuzzy robust strategy composed of the fuzzy switched strategy and the fuzzy control strategy can guarantee the robust operation of the supply chain network at low cost. Finally, the simulation researches show the advantage of the proposed fuzzy robust strategy through the comparisons with the common robust strategy.

Suggested Citation

  • Songtao Zhang & Chunyang Zhang & Siqi Zhang & Min Zhang, 2018. "Discrete Switched Model and Fuzzy Robust Control of Dynamic Supply Chain Network," Complexity, Hindawi, vol. 2018, pages 1-11, January.
  • Handle: RePEc:hin:complx:3495096
    DOI: 10.1155/2018/3495096
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    References listed on IDEAS

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    1. Roba W. Salem & Mohamed Haouari, 2017. "A simulation-optimisation approach for supply chain network design under supply and demand uncertainties," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 1845-1861, April.
    2. Govindan, Kannan & Fattahi, Mohammad, 2017. "Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case study of glass supply chain," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 680-699.
    3. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
    4. 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.
    5. Haddadsisakht, Ali & Ryan, Sarah M., 2018. "Closed-loop supply chain network design with multiple transportation modes under stochastic demand and uncertain carbon tax," International Journal of Production Economics, Elsevier, vol. 195(C), pages 118-131.
    6. Nima Hamta & M. Akbarpour Shirazi & S.M.T. Fatemi Ghomi & Sara Behdad, 2015. "Supply chain network optimization considering assembly line balancing and demand uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 53(10), pages 2970-2994, May.
    7. Erdem Eskigun & Reha Uzsoy & Paul V. Preckel & George Beaujon & Subramanian Krishnan & Jeffrey D. Tew, 2007. "Outbound supply chain network design with mode selection and lead time considerations," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(3), pages 282-300, April.
    8. Fattahi, Mohammad & Govindan, Kannan & Keyvanshokooh, Esmaeil, 2017. "Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 176-200.
    9. Larsen, Erik R. & Morecroft, John D. W. & Thomsen, Jesper S., 1999. "Complex behaviour in a production-distribution model," European Journal of Operational Research, Elsevier, vol. 119(1), pages 61-74, November.
    10. Ambrosino, Daniela & Grazia Scutella, Maria, 2005. "Distribution network design: New problems and related models," European Journal of Operational Research, Elsevier, vol. 165(3), pages 610-624, September.
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