A stochastic model for risk management in global supply chain networks

2007 ◽  
Vol 182 (1) ◽  
pp. 164-173 ◽  
Author(s):  
Mark Goh ◽  
Joseph Y.S. Lim ◽  
Fanwen Meng
Author(s):  
Anna Nagurney ◽  
José M. Cruz ◽  
June Dong

Author(s):  
Tan Miller ◽  
Renato de Matta

Developing integrated strategic, tactical and operational manufacturing and distribution plans for the global supply chain of a large, international firm represents a formidable planning, as well as organizational undertaking. Moreover, to develop and execute plans that are not only integrated, but which maximize profits on a global basis presents a challenge of far greater magnitude. The use of advanced optimization modeling based analytics can generate keen insights for management decisions regarding sourcing, production, distribution, inventory and demand management on supply chain networks. This includes scenario and contingency planning analyses of complex strategic trade-offs such as the optimal balance between inventory levels and reserve manufacturing capacity on a network. In this chapter, we illustrate how optimization models can support a firm's planning efforts for these and related supply chain business decisions.


Author(s):  
Dimitrios Vlachos

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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