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An agent-based negotiation model on price and delivery date in a fashion supply chain

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  • An Pan

    (The Hong Kong Polytechnic University)

  • Tsan-Ming Choi

    (The Hong Kong Polytechnic University)

Abstract

Price and due-date negotiation between supply chain members is a critical issue. Motivated by industrial practice, we consider in this paper a make-to-order fashion supply chain in which the downstream manufacturer and the upstream supplier are cooperative on due-date and competitive on price. We propose a two-phase negotiation agenda based on such characteristics, and aim to find an optimal solution to deal with the negotiation problem considering production cost and mutual benefit. We build an analytical negotiation model for a manufacturer-supplier pair, discuss their utilities, and examine the Pareto efficiency frontier from the theoretical perspective. After that, from an application perspective, we build an agent-based two-phase negotiation system where agents are used to represent the two parties to enhance communication. In the cooperative phase, a simulated annealing based intelligent algorithm is employed to help the manufacturer agent and the supplier agent search tentative agreement on due dates which can minimize the total supply chain cost. In the competitive phase, the two parties bargain on the pricing issue using concession based methods. They adjust the reservation value and aspiration value for pricing accordingly based on the integrated utility and the result of the previous phase. Simulation results show that, the proposed negotiation approach can achieve optimal utility of agents and reach a win-win situation for the bilateral parties. Sensitivity analysis is conducted to further generate insights on how different parameters affect the performance of the proposed system.

Suggested Citation

  • An Pan & Tsan-Ming Choi, 2016. "An agent-based negotiation model on price and delivery date in a fashion supply chain," Annals of Operations Research, Springer, vol. 242(2), pages 529-557, July.
    • Handle: RePEc:spr:annopr:v:242:y:2016:i:2:d:10.1007_s10479-013-1327-2
    DOI: 10.1007/s10479-013-1327-2
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    Cited by:

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    2. Ata Allah Taleizadeh, 2017. "Stochastic Multi-Objectives Supply Chain Optimization with Forecasting Partial Backordering Rate: A Novel Hybrid Method of Meta Goal Programming and Evolutionary Algorithms," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(04), pages 1-28, August.
    3. Mahmoud Dehghan Nayeri & Amir-Nader Haghbin & Abdolkarim Mohammadi-Balani & Karim Bayat, 2020. "A multi-objective mean–variance mathematical programming approach to combined phase-out and clearance pricing strategy for seasonal products: case study of a Jeans retailer," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(3), pages 210-217, June.
    4. Juan Du & Hengqing Jing & Kim-Kwang Raymond Choo & Vijayan Sugumaran & Daniel Castro-Lacouture, 2020. "An Ontology and Multi-Agent Based Decision Support Framework for Prefabricated Component Supply Chain," Information Systems Frontiers, Springer, vol. 22(6), pages 1467-1485, December.
    5. Victor Dragotă & Camelia Delcea, 2019. "How Long Does It Last to Systematically Make Bad Decisions? An Agent-Based Application for Dividend Policy," JRFM, MDPI, vol. 12(4), pages 1-34, November.
    6. Juan Du & Hengqing Jing & Kim-Kwang Raymond Choo & Vijayan Sugumaran & Daniel Castro-Lacouture, 0. "An Ontology and Multi-Agent Based Decision Support Framework for Prefabricated Component Supply Chain," Information Systems Frontiers, Springer, vol. 0, pages 1-19.
    7. Barenji, Ali Vatankhah & Wang, W.M. & Li, Zhi & Guerra-Zubiaga, David A., 2019. "Intelligent E-commerce logistics platform using hybrid agent based approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 15-31.
    8. Yue Chen & Sai-Ho Chung & Shu Guo, 2020. "Franchising contracts in fashion supply chain operations: models, practices, and real case study," Annals of Operations Research, Springer, vol. 291(1), pages 83-128, August.
    9. Heng Du & Tiaojun Xiao, 2019. "Pricing Strategies for Competing Adaptive Retailers Facing Complex Consumer Behavior: Agent-based Model," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(06), pages 1909-1939, November.
    10. Kannan Govindan, 2016. "Evolutionary algorithms for supply chain management," Annals of Operations Research, Springer, vol. 242(2), pages 195-206, July.
    11. Amirhosein Gholami & Nasim Nezamoddini & Mohammad T. Khasawneh, 2023. "Customized orders management in connected make-to-order supply chains," Operations Management Research, Springer, vol. 16(3), pages 1428-1443, September.

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