Optimal replenishment under price uncertainty


Mohr, Esther



DOI: https://doi.org/10.1016/j.ejor.2016.08.011
URL: http://www.sciencedirect.com/science/article/pii/S...
Additional URL: https://www.researchgate.net/publication/306074494...
Document Type: Article
Year of publication: 2017
The title of a journal, publication series: European Journal of Operational Research : EJOR
Volume: 258
Issue number: 1
Page range: 136-143
Place of publication: Amsterdam
Publishing house: Elsevier
ISSN: 0377-2217
Publication language: English
Institution: Business School > ABWL u. Service Operations (Schön 2014-)
Subject: 330 Economics
Keywords (English): Inventory ; Online algorithms ; Minimax regret ; Competitive ratio ; Optimal search
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.

Dieser Eintrag ist Teil der Universitätsbibliographie.




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Mohr, Esther (2017) Optimal replenishment under price uncertainty. European Journal of Operational Research : EJOR Amsterdam 258 1 136-143 [Article]


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