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Dynamic supply chain modeling using a new fuzzy hybrid negotiation mechanism

Author

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  • Jain, Vipul
  • Deshmukh, S.G.

Abstract

The key part of dynamic supply chain management is negotiating with suppliers and with buyers. Coordination is essential for successful supply chain management. In order to model coordination among suppliers and buyers in a dynamic supply chain, this paper takes a step further and proposes a new fuzzy- logic-based hybrid negotiation mechanism. In most real-world negotiation situations, agents have a common interest to cooperate, but have conflicting interests over exactly how to cooperate. These situations involve restrictions and preferences that may be vaguely and partly defined. Therefore, this study takes the advantage of fuzzy logic and develops a hybrid negotiation-based mechanism, that combines both cooperative and competitive negotiations. Achieving effective coordination in a multi-agent system is non-trivial as no agent possesses the global view of the problem space. Moreover, the different strategies adopted by agents may produce conflicts. While agents coordinate with each other in the operations, they will negotiate about their strategies to reduce conflicts. The proposed fuzzy hybrid negotiation mechanism allows negotiation agents more flexibility and robustness in an automated negotiation system. The proposed mechanism not only helps sellers and buyers to explore various new choices and opportunities that the e-markets offer but also allows them to identify and analyze their resource constraints in a given schedule, and helps them to explore and exploit many alternatives for a better solution. The efficacy of the proposed approach is demonstrated through an illustrative example.

Suggested Citation

  • Jain, Vipul & Deshmukh, S.G., 2009. "Dynamic supply chain modeling using a new fuzzy hybrid negotiation mechanism," International Journal of Production Economics, Elsevier, vol. 122(1), pages 319-328, November.
  • Handle: RePEc:eee:proeco:v:122:y:2009:i:1:p:319-328
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    References listed on IDEAS

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    1. Vipul Jain & S. Wadhwa & S.G. Deshmukh, 2006. "Modelling and analysis of supply chain dynamics: a High Intelligent Time (HIT) petri net based approach," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 1(1/2), pages 59-86.
    2. Frayret, Jean-Marc & D&rsquo & Amours, Sophie & Montreuil, Benoit & Cloutier, Louis, 2001. "A network approach to operate agile manufacturing systems," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 239-259, December.
    3. Petrovic, Dobrila & Roy, Rajat & Petrovic, Radivoj, 1999. "Supply chain modelling using fuzzy sets," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 443-453, March.
    4. Vipul Jain & S. Wadhwa & S. G. Deshmukh, 2007. "A Negotiation-to-Coordinate (N2C) Mechanism for Modeling Buyer-Supplier Relationship in Dynamic Environment," International Journal of Enterprise Information Systems (IJEIS), IGI Global, vol. 3(2), pages 1-22, April.
    5. D'Amours, Sophie & Montreuil, Benoit & Lefrancois, Pierre & Soumis, Francois, 1999. "Networked manufacturing:: The impact of information sharing," International Journal of Production Economics, Elsevier, vol. 58(1), pages 63-79, January.
    6. Reaidy, Jihad & Massotte, Pierre & Diep, Daniel, 2006. "Comparison of negotiation protocols in dynamic agent-based manufacturing systems," International Journal of Production Economics, Elsevier, vol. 99(1-2), pages 117-130, February.
    7. N.R. Jennings & P. Faratin & A.R. Lomuscio & S. Parsons & M.J. Wooldridge & C. Sierra, 2001. "Automated Negotiation: Prospects, Methods and Challenges," Group Decision and Negotiation, Springer, vol. 10(2), pages 199-215, March.
    8. Yoo, Sang Bong & Kim, Yeongho, 2002. "Web-based knowledge management for sharing product data in virtual enterprises," International Journal of Production Economics, Elsevier, vol. 75(1-2), pages 173-183, January.
    9. Lo, Wei-Shuo & Hong, Tzung-Pei & Jeng, Rong, 2008. "A framework of E-SCM multi-agent systems in the fashion industry," International Journal of Production Economics, Elsevier, vol. 114(2), pages 594-614, August.
    10. Yunzeng Wang & Yigal Gerchak, 2001. "Supply Chain Coordination when Demand Is Shelf-Space Dependent," Manufacturing & Service Operations Management, INFORMS, vol. 3(1), pages 82-87, August.
    11. Terry A. Taylor, 2001. "Channel Coordination Under Price Protection, Midlife Returns, and End-of-Life Returns in Dynamic Markets," Management Science, INFORMS, vol. 47(9), pages 1220-1234, September.
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    Cited by:

    1. Gajanan Panchal & Vipul Jain & Naoufel Cheikhrouhou & Matthias Gurtner, 2017. "Equilibrium analysis in multi-echelon supply chain with multi-dimensional utilities of inertial players," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(4), pages 417-436, August.
    2. Ge, Houtian & Gray, Richard & Nolan, James, 2015. "Agricultural supply chain optimization and complexity: A comparison of analytic vs simulated solutions and policies," International Journal of Production Economics, Elsevier, vol. 159(C), pages 208-220.
    3. Mejía, Gonzalo & García-Díaz, César, 2018. "Market-level effects of firm-level adaptation and intermediation in networked markets of fresh foods: A case study in Colombia," Agricultural Systems, Elsevier, vol. 160(C), pages 132-142.
    4. Azadegan, Arash & Porobic, Lejla & Ghazinoory, Sepehr & Samouei, Parvaneh & Saman Kheirkhah, Amir, 2011. "Fuzzy logic in manufacturing: A review of literature and a specialized application," International Journal of Production Economics, Elsevier, vol. 132(2), pages 258-270, August.

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