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Optimal pricing and lot-sizing for perishable inventory with price and time dependent ramp-type demand

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  • S. Panda
  • S. Saha
  • M. Basu

Abstract

Product perishability is an important aspect of inventory control. To minimise the effect of deterioration, retailers in supermarkets, departmental store managers, etc. always want higher inventory depletion rate. In this article, we propose a dynamic pre- and post-deterioration cumulative discount policy to enhance inventory depletion rate resulting low volume of deterioration cost, holding cost and hence higher profit. It is assumed that demand is a price and time dependent ramp-type function and the product starts to deteriorate after certain amount of time. Unlike the conventional inventory models with pricing strategies, which are restricted to a fixed number of price changes and to a fixed cycle length, we allow the number of price changes before as well as after the start of deterioration and the replenishment cycle length to be the decision variables. Before start of deterioration, discounts on unit selling price are provided cumulatively in successive pricing cycles. After the start of deterioration, discounts on reduced unit selling price are also provided in a cumulative way. A mathematical model is developed and the existence of the optimal solution is verified. A numerical example is presented, which indicates that under the cumulative effect of price discounting, dynamic pricing policy outperforms static pricing strategy. Sensitivity analysis of the model is carried out.

Suggested Citation

  • S. Panda & S. Saha & M. Basu, 2013. "Optimal pricing and lot-sizing for perishable inventory with price and time dependent ramp-type demand," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(1), pages 127-138.
  • Handle: RePEc:taf:tsysxx:v:44:y:2013:i:1:p:127-138
    DOI: 10.1080/00207721.2011.598956
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    Cited by:

    1. Ghavamifar, Ali & Makui, Ahmad & Taleizadeh, Ata Allah, 2018. "Designing a resilient competitive supply chain network under disruption risks: A real-world application," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 87-109.
    2. Terzi, Mourad & Ouazene, Yassine & Yalaoui, Alice & Yalaoui, Farouk, 2023. "Lot-sizing and pricing decisions under attraction demand models and multi-channel environment: New efficient formulations," Operations Research Perspectives, Elsevier, vol. 10(C).
    3. R. Ghasemy Yaghin & S.M.T. Fatemi Ghomi & S.A. Torabi, 2015. "A hybrid credibility-based fuzzy multiple objective optimisation to differential pricing and inventory policies with arbitrage consideration," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(14), pages 2628-2639, October.
    4. Modak, Nikunja Mohan & Panda, Shibaji & Sana, Shib Sankar, 2016. "Three-echelon supply chain coordination considering duopolistic retailers with perfect quality products," International Journal of Production Economics, Elsevier, vol. 182(C), pages 564-578.
    5. Zhang, Jianxiong & Liu, Guowei & Zhang, Qiao & Bai, Zhenyu, 2015. "Coordinating a supply chain for deteriorating items with a revenue sharing and cooperative investment contract," Omega, Elsevier, vol. 56(C), pages 37-49.
    6. Dai, Zhuo & Aqlan, Faisal & Gao, Kuo, 2017. "Optimizing multi-echelon inventory with three types of demand in supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 107(C), pages 141-177.
    7. Rabbani, Masoud & Pourmohammad Zia, Nadia & Rafiei, Hamed, 2016. "Joint optimal dynamic pricing and replenishment policies for items with simultaneous quality and physical quantity deterioration," Applied Mathematics and Computation, Elsevier, vol. 287, pages 149-160.
    8. Saha, Subrata & Sarkar, Biswajit & Sarkar, Mitali, 2023. "Application of improved meta-heuristic algorithms for green preservation technology management to optimize dynamical investments and replenishment strategies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 209(C), pages 426-450.

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