Optimal ordering policies in a multi-sourcing supply chain with supply and demand disruptions-a CVaR approach

Optimal ordering policies in a multi-sourcing supply chain with supply and demand disruptions-a CVaR approach

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Article ID: iaor20174311
Volume: 28
Issue: 2
Start Page Number: 180
End Page Number: 199
Publication Date: Sep 2017
Journal: International Journal of Logistics Systems and Management
Authors: ,
Keywords: supply & supply chains, inventory, combinatorial optimization, optimization, demand, simulation, probability, decision, economics
Abstract:

In this study, we propose a conditional value at risk (CVaR) model for supply chain disruptions planning of a multi‐agent, multi‐product supply chain subject to supply and demand disruptions. Our focus is on building and comparing ordering policies under CVaR and expected cost criteria. The proposed formulation is illustrated through some numerical instances. The results present that the CVaR model shows a considerable difference in response policies compared to the expected cost model. Ordering quantities in response to supply and demand disruption are lower in the CVaR model than the expected cost model. In many instances, it is also seen that ordering quantities in response to disruptions tend to become lower when a decision maker becomes more risk‐averse. It is expected that the proposed CVaR model would outperform to optimise the supply chain of an organisation, in particular, for the purpose of reducing the risk of high cost.

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