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Dynamic pricing and replenishment in the warehouse scheduling problem--A common cycle approach

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  • Transchel, Sandra
  • Minner, Stefan

Abstract

In this paper, we consider the problem at the interface of marketing and operations to find the optimal lot-size and selling price for multiple products that share a warehouse with limited storage capacity. We analyze the impact of coordinated decision making on the selling price and the replenishment policy compared to a decentralized decision. Furthermore, we compare constant pricing where the selling price remains constant over the entire planning horizon and dynamic pricing where the firm is allowed to adjust the selling price continuously. The objective is to maximize the average profit by choosing the optimal pricing strategy, the optimal lot-sizes, and the optimal staggering of the order releases. This paper provides both analytical and numerical results on the impact of a joint optimization on the pricing and replenishment decisions and the potential benefits compared to the decentralized approach. We develop mathematical models for the different decision frameworks, provide algorithms to determine the optimal policy parameters, and show that the peak storage requirement is equal at each replenishment. Furthermore, we show in a numerical example that achieving operational efficiency through dynamic pricing in the warehouse scheduling problem is even more beneficial than in the economic order quantity framework.

Suggested Citation

  • Transchel, Sandra & Minner, Stefan, 2009. "Dynamic pricing and replenishment in the warehouse scheduling problem--A common cycle approach," International Journal of Production Economics, Elsevier, vol. 118(1), pages 331-338, March.
  • Handle: RePEc:eee:proeco:v:118:y:2009:i:1:p:331-338
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    References listed on IDEAS

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    1. Wedad Elmaghraby & P{i}nar Keskinocak, 2003. "Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions," Management Science, INFORMS, vol. 49(10), pages 1287-1309, October.
    2. Arvind Rajan & Richard Rakesh, 1992. "Dynamic Pricing and Ordering Decisions by a Monopolist," Management Science, INFORMS, vol. 38(2), pages 240-262, February.
    3. Dov Pekelman, 1974. "Simultaneous Price-Production Decisions," Operations Research, INFORMS, vol. 22(4), pages 788-794, August.
    4. T. M. Whitin, 1955. "Inventory Control and Price Theory," Management Science, INFORMS, vol. 2(1), pages 61-68, October.
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    Cited by:

    1. Lin, Xuxun & Wang, Haiyan, 2022. "Dynamic pricing for online information services considering service duration and quality level," Omega, Elsevier, vol. 109(C).
    2. Zhang, Guoqing & Nishi, Tatsushi & Turner, Sarina D.O. & Oga, Keisuke & Li, Xindan, 2017. "An integrated strategy for a production planning and warehouse layout problem: Modeling and solution approaches," Omega, Elsevier, vol. 68(C), pages 85-94.
    3. Zhang, Guoqing & Shang, Xiaoting & Alawneh, Fawzat & Yang, Yiqin & Nishi, Tatsushi, 2021. "Integrated production planning and warehouse storage assignment problem: An IoT assisted case," International Journal of Production Economics, Elsevier, vol. 234(C).
    4. Buisman, M.E. & Haijema, R. & Bloemhof-Ruwaard, J.M., 2019. "Discounting and dynamic shelf life to reduce fresh food waste at retailers," International Journal of Production Economics, Elsevier, vol. 209(C), pages 274-284.

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