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Risk management policies for dynamic capacity control

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Risk management policies for dynamic capacity control. / Koenig, Matthias; Meissner, Joern.
In: Computers and Operations Research, Vol. 59, 07.2015, p. 104-118.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Koenig, M & Meissner, J 2015, 'Risk management policies for dynamic capacity control', Computers and Operations Research, vol. 59, pp. 104-118. https://doi.org/10.1016/j.cor.2014.12.004

APA

Koenig, M., & Meissner, J. (2015). Risk management policies for dynamic capacity control. Computers and Operations Research, 59, 104-118. https://doi.org/10.1016/j.cor.2014.12.004

Vancouver

Koenig M, Meissner J. Risk management policies for dynamic capacity control. Computers and Operations Research. 2015 Jul;59:104-118. Epub 2015 Jan 6. doi: 10.1016/j.cor.2014.12.004

Author

Koenig, Matthias ; Meissner, Joern. / Risk management policies for dynamic capacity control. In: Computers and Operations Research. 2015 ; Vol. 59. pp. 104-118.

Bibtex

@article{7e1e18265a9c45099263f2f2aa5cfe8c,
title = "Risk management policies for dynamic capacity control",
abstract = "Abstract Consider a dynamic decision making model under risk with a fixed planning horizon, namely the dynamic capacity control model. The model describes a firm, operating in a monopolistic setting and selling a range of products consuming a single resource. Demand for each product is time-dependent and modeled by a random variable. The firm controls the revenue stream by allowing or denying customer requests for product classes. We investigate risk-sensitive policies in this setting, for which risk concerns are important for many non-repetitive events and short-time considerations. Numerically analysing several risk-averse capacity control policies in terms of standard deviation and conditional-value-at-risk, our results show that only a slight modification of the risk-neutral solution is needed to apply a risk-averse policy. In particular, risk-averse policies which decision rules are functions depending only on the marginal values of the risk-neutral policy perform well. From a practical perspective, the advantage is that a decision maker does not need to compute any risk-averse dynamic program. Risk sensitivity can be easily achieved by implementing risk-averse functional decision rules based on a risk-neutral solution.",
keywords = "Dynamic decisions, Capacity control, Revenue management, Risk",
author = "Matthias Koenig and Joern Meissner",
year = "2015",
month = jul,
doi = "10.1016/j.cor.2014.12.004",
language = "English",
volume = "59",
pages = "104--118",
journal = "Computers and Operations Research",
issn = "0305-0548",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - Risk management policies for dynamic capacity control

AU - Koenig, Matthias

AU - Meissner, Joern

PY - 2015/7

Y1 - 2015/7

N2 - Abstract Consider a dynamic decision making model under risk with a fixed planning horizon, namely the dynamic capacity control model. The model describes a firm, operating in a monopolistic setting and selling a range of products consuming a single resource. Demand for each product is time-dependent and modeled by a random variable. The firm controls the revenue stream by allowing or denying customer requests for product classes. We investigate risk-sensitive policies in this setting, for which risk concerns are important for many non-repetitive events and short-time considerations. Numerically analysing several risk-averse capacity control policies in terms of standard deviation and conditional-value-at-risk, our results show that only a slight modification of the risk-neutral solution is needed to apply a risk-averse policy. In particular, risk-averse policies which decision rules are functions depending only on the marginal values of the risk-neutral policy perform well. From a practical perspective, the advantage is that a decision maker does not need to compute any risk-averse dynamic program. Risk sensitivity can be easily achieved by implementing risk-averse functional decision rules based on a risk-neutral solution.

AB - Abstract Consider a dynamic decision making model under risk with a fixed planning horizon, namely the dynamic capacity control model. The model describes a firm, operating in a monopolistic setting and selling a range of products consuming a single resource. Demand for each product is time-dependent and modeled by a random variable. The firm controls the revenue stream by allowing or denying customer requests for product classes. We investigate risk-sensitive policies in this setting, for which risk concerns are important for many non-repetitive events and short-time considerations. Numerically analysing several risk-averse capacity control policies in terms of standard deviation and conditional-value-at-risk, our results show that only a slight modification of the risk-neutral solution is needed to apply a risk-averse policy. In particular, risk-averse policies which decision rules are functions depending only on the marginal values of the risk-neutral policy perform well. From a practical perspective, the advantage is that a decision maker does not need to compute any risk-averse dynamic program. Risk sensitivity can be easily achieved by implementing risk-averse functional decision rules based on a risk-neutral solution.

KW - Dynamic decisions

KW - Capacity control

KW - Revenue management

KW - Risk

U2 - 10.1016/j.cor.2014.12.004

DO - 10.1016/j.cor.2014.12.004

M3 - Journal article

VL - 59

SP - 104

EP - 118

JO - Computers and Operations Research

JF - Computers and Operations Research

SN - 0305-0548

ER -