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Quantitative Risk Management Models for Newsvendor Supply Chains

Quantitative Risk Management Models for Newsvendor Supply Chains

Dimitrios Vlachos
Copyright: © 2011 |Pages: 16
ISBN13: 9781615206339|ISBN10: 1615206337|EISBN13: 9781615206346
DOI: 10.4018/978-1-61520-633-9.ch007
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MLA

Vlachos, Dimitrios. "Quantitative Risk Management Models for Newsvendor Supply Chains." Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods, edited by Ioannis Minis, et al., IGI Global, 2011, pp. 155-170. https://doi.org/10.4018/978-1-61520-633-9.ch007

APA

Vlachos, D. (2011). Quantitative Risk Management Models for Newsvendor Supply Chains. In I. Minis, V. Zeimpekis, G. Dounias, & N. Ampazis (Eds.), Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods (pp. 155-170). IGI Global. https://doi.org/10.4018/978-1-61520-633-9.ch007

Chicago

Vlachos, Dimitrios. "Quantitative Risk Management Models for Newsvendor Supply Chains." In Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods, edited by Ioannis Minis, et al., 155-170. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-61520-633-9.ch007

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Abstract

As the practices of offshoring and outsourcing force the supply chain networks to keep on expanding geographically in the globalised environment, the logistics processes are becoming more exposed to risk and disruptions. Thus, modern supply chains seem to be more vulnerable than ever. It is clear that efficient logistics risk and security management emerges as an issue of pivotal importance in such competitive, demanding and stochastic environment and is thus vital for the viability and profitability of a company. In this context, this chapter focuses on a set of stochastic quantitative models that study the impact of one or more supply chain disruptions on optimal determination of single period inventory control policies. The purpose of this research is to provide a critical review of state-of-the-art methodologies to be used as a starting point for further research efforts.

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