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Dynamic pricing model and algorithm for perishable products with fuzzy demand

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  • Yu Xiong
  • Gendao Li
  • Kiran Jude Fernandes

Abstract

This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, α‐optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real‐world example is presented to highlight the effectiveness of the developed model and algorithm. Copyright © 2009 John Wiley & Sons, Ltd.

Suggested Citation

  • Yu Xiong & Gendao Li & Kiran Jude Fernandes, 2010. "Dynamic pricing model and algorithm for perishable products with fuzzy demand," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(6), pages 758-774, November.
    • Handle: RePEc:wly:apsmbi:v:26:y:2010:i:6:p:758-774
    DOI: 10.1002/asmb.816
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    Cited by:

    1. Bo Yan & Jiwen Wu & Zijie Jin & Shiyou He, 2020. "Decision-making of fresh agricultural product supply chain considering the manufacturer’s fairness concerns," 4OR, Springer, vol. 18(1), pages 91-122, March.
    2. Jing Xu & Shihao Xiong & Tingyu Cui & Dongmei Zhang & Zhibin Li, 2023. "Incorporating Consumers’ Low-Carbon and Freshness Preferences in Dual-Channel Agri-Foods Supply Chains: An Analysis of Decision-Making Behavior," Agriculture, MDPI, vol. 13(9), pages 1-19, August.
    3. Peter Seele & Claus Dierksmeier & Reto Hofstetter & Mario D. Schultz, 2021. "Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing," Journal of Business Ethics, Springer, vol. 170(4), pages 697-719, May.

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