Rights statement: This is the author’s version of a work that was accepted for publication in European Journal of Operatoinal Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Jourrnal of Operational Research, 300, 2, 2022 DOI: 10.1016/j.ejor.2021.08.013
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Newsvendor problems
T2 - An integrated method for estimation and optimisation
AU - Liu, Congzheng
AU - Letchford, Adam
AU - Svetunkov, Ivan
N1 - This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 300(2), 590-601, 2021. DOI: 10.1016/j.ejor.2021.08.013
PY - 2022/7/16
Y1 - 2022/7/16
N2 - Newsvendor problems (NVP) form a classical and important family of stochastic optimisation problems. In this paper, we consider a data-driven solution method proposed recently by Ban and Rudin. We first examine it from a statistical viewpoint, and establish a connection with quantile regression. We then extend the approach to nonlinear NVP. Finally, we give extensive experimental results, on both simulated and real data. The results indicate that the approach performs as well as conventional ones when applied to linear NVP, but performs better when applied to nonlinear NVP. There is also evidence that the approach is more robust with respect to model misspecification.
AB - Newsvendor problems (NVP) form a classical and important family of stochastic optimisation problems. In this paper, we consider a data-driven solution method proposed recently by Ban and Rudin. We first examine it from a statistical viewpoint, and establish a connection with quantile regression. We then extend the approach to nonlinear NVP. Finally, we give extensive experimental results, on both simulated and real data. The results indicate that the approach performs as well as conventional ones when applied to linear NVP, but performs better when applied to nonlinear NVP. There is also evidence that the approach is more robust with respect to model misspecification.
KW - inventory control
KW - newsvendor problems
KW - optimisation
U2 - 10.1016/j.ejor.2021.08.013
DO - 10.1016/j.ejor.2021.08.013
M3 - Journal article
VL - 300
SP - 590
EP - 601
JO - European Journal of Operational Research
JF - European Journal of Operational Research
SN - 0377-2217
IS - 2
ER -