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Optimal replenishment under price uncertainty

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  • Mohr, Esther

Abstract

We aim to find optimal replenishment decisions without having the entire price information available at the outset. Although it exists, the underlying price distribution is neither known nor given as part of the input. Under the competitive ratio optimality criterion, we design and analyze online algorithms for two related problems. Besides the reservation price based decision how much to buy we additionally consider the optimal scheduling of orders. We suggest an online algorithm that decides how much to buy at the optimal point in time and experimentally explore its decision making. Results show that the problem of finding a replenishment strategy with best possible worst-case performance guarantees can be considered as an extension of the online time series search problem.

Suggested Citation

  • Mohr, Esther, 2017. "Optimal replenishment under price uncertainty," European Journal of Operational Research, Elsevier, vol. 258(1), pages 136-143.
    • Handle: RePEc:eee:ejores:v:258:y:2017:i:1:p:136-143
    DOI: 10.1016/j.ejor.2016.08.011
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    References listed on IDEAS

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    Cited by:

    1. Wenqiang Dai & Meng Zheng & Xu Chen & Zhuolin Yang, 0. "Online economic ordering problem for deteriorating items with limited price information," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-23.
    2. Wang, Wei & Lan, Yingjie, 2022. "Robust one-way trading with limited number of transactions and heuristics for fixed transaction costs," International Journal of Production Economics, Elsevier, vol. 247(C).
    3. Wenqiang Dai & Meng Zheng & Xu Chen & Zhuolin Yang, 2022. "Online economic ordering problem for deteriorating items with limited price information," Journal of Combinatorial Optimization, Springer, vol. 44(4), pages 2246-2268, November.

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