A Maximum Entropy Joint Demand Estimation and Capacity Control Policy
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Cited by:
- Gönsch, Jochen, 2017. "A survey on risk-averse and robust revenue management," European Journal of Operational Research, Elsevier, vol. 263(2), pages 337-348.
- Boxiao Chen & Xiuli Chao & Cong Shi, 2021. "Nonparametric Learning Algorithms for Joint Pricing and Inventory Control with Lost Sales and Censored Demand," Mathematics of Operations Research, INFORMS, vol. 46(2), pages 726-756, May.
- Jiri Chod & Mihalis G. Markakis & Nikolaos Trichakis, 2021. "On the Learning Benefits of Resource Flexibility," Management Science, INFORMS, vol. 67(10), pages 6513-6528, October.
- Fleischhacker, Adam J. & Fok, Pak-Wing, 2015. "On the relationship between entropy, demand uncertainty, and expected loss," European Journal of Operational Research, Elsevier, vol. 245(2), pages 623-628.
- Cong Shi & Weidong Chen & Izak Duenyas, 2016. "Technical Note—Nonparametric Data-Driven Algorithms for Multiproduct Inventory Systems with Censored Demand," Operations Research, INFORMS, vol. 64(2), pages 362-370, April.
- Soroush Saghafian & Brian Tomlin, 2016. "The Newsvendor under Demand Ambiguity: Combining Data with Moment and Tail Information," Operations Research, INFORMS, vol. 64(1), pages 167-185, February.
- Zizhuo Wang & Chaolin Yang & Hongsong Yuan & Yaowu Zhang, 2021. "Aggregation Bias in Estimating Log‐Log Demand Function," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 3906-3922, November.
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