Global Supply Chain Networks and Risk Management: A Multi-Agent Framework

2006 ◽  
pp. 103-134 ◽  
Author(s):  
Anna Nagurney ◽  
Anna Nagurney ◽  
Jose M. Cruz ◽  
June Dong
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Global Supply Chain ◽  
Supply Chain Networks ◽  
Multi Agent

A Multi-Agent-Based Research on Tourism Supply Chain Risk Management

2014 ◽  
Vol 13 (03) ◽  
pp. 133-153 ◽  
Author(s):  
Luo Biao ◽  
Wan Liang ◽  
Liang Liang
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Tourism Industry ◽  
Limiting Factors ◽  
Supply Chain Risk Management ◽  
Agent Based ◽  
Research Perspective ◽  
Multi Agent ◽  
High Level ◽  
Tourism Supply Chain

The high level of complexity of tourism supply chain and the inherent risks that exist in the demand and supply of resources are viewed as major limiting factors in achieving high level performance. Though emerging literature on risk management in tourism industry or its equivalent exists, progress in this area is uneven, as most research focuses on this problem from the traditional single business risk management perspective, without considering the entire range of different suppliers involved in the provision and consumption of tourism products. This study applies risk management theory to a new research perspective, which is tourism supply chain management (SCM). This paper develops a framework for the design of a multi-agent-based decision support system (DSS) based on multi-agent theory and technique, in order to manage disruptions and mitigate risks in tourism supply chain.

Profit Maximizing Network Modeling With Inventory and Capacity Considerations

2018 ◽  
pp. 5503-5515
Author(s):  
Tan Miller ◽  
Renato de Matta
Keyword(s):  
Supply Chain ◽  
Network Modeling ◽  
Demand Management ◽  
Global Supply Chain ◽  
Optimization Models ◽  
Business Decisions ◽  
Supply Chain Networks ◽  
Strategic Trade ◽  
Trade Offs ◽  
Production Distribution

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.

Quantitative Risk Management Models for Newsvendor Supply Chains

2011 ◽  
pp. 155-170
Author(s):  
Dimitrios Vlachos
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Supply Chains ◽  
Stochastic Environment ◽  
Supply Chain Disruptions ◽  
Supply Chain Networks ◽  
Starting Point ◽  
The Impact ◽  
A Company

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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