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Joint dynamic pricing and lot-sizing under competition

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  • Alejandro Lamas
  • Philippe Chevalier

Abstract

We study the joint dynamic pricing and lot-sizing problem when firms operate in a competitive environment. Bearing in mind that a dynamic pricing strategy is successful when customers understand it, we assume each firm selects prices from a discrete set. The problem corresponds to a Bertrand model, so the pricing strategies of the firms should constitute a Nash Equilibrium. Given the combinatorial nature of the decisions, computing the equilibrium in a tractable time may not be feasible for larger instances. In order to compute the equilibrium efficiently, we propose a framework consisting of solving iteratively Mixed Integer Programming formulations. The framework reduces the complexity of the problem by using the fact that pricing and inventory planning remain stable to marginal variations in competitors’ prices.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Alejandro Lamas & Philippe Chevalier, 2018. "Joint dynamic pricing and lot-sizing under competition," LIDAM Reprints CORE 2938, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvrp:2938
    Note: In : European Journal of Operations Research, 266, 864-876, 2018
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    Cited by:

    1. Ma, Junhai & Si, Fengshan & Zhang, Qin & Wang, Zongxian, 2024. "Impact of extended warranty service on product pricing in online direct retailers' competitive market," Energy Economics, Elsevier, vol. 129(C).
    2. Claudio Telha & Margarida Carvalho, 2025. "Integration of Sales and Operations: A Dynamic Mixed-Integer Programming Game," Dynamic Games and Applications, Springer, vol. 15(1), pages 306-328, March.
    3. Gao, Kaiye & Peng, Rui & Qu, Li & Wu, Shaomin, 2020. "Jointly optimizing lot sizing and maintenance policy for a production system with two failure modes," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    4. Qiu, Ruozhen & Sun, Yue & Zhou, Hongcheng & Sun, Minghe, 2023. "Dynamic pricing and quick response of a retailer in the presence of strategic consumers: A distributionally robust optimization approach," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1270-1298.
    5. Li, Mengmeng & Mizuno, Shinji, 2022. "Comparison of dynamic and static pricing strategies in a dual-channel supply chain with inventory control," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    6. Liu, Yezheng & Qian, Yang & Jiang, Yuanchun & Shang, Jennifer, 2020. "Using favorite data to analyze asymmetric competition: Machine learning models," European Journal of Operational Research, Elsevier, vol. 287(2), pages 600-615.

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