Title: Optimizing efficiency‐robustness trade‐offs in supply chain design under uncertainty due to disruptions
Abstract: Purpose Supply chain network design is an important strategic decision that firms make considering both the short‐ and long‐term consequences of the network's performance. The typical design approach implicitly assumes that, once designed, the facilities and the links will always operate as planned. In reality, however, facilities and the links connecting them, fail from time to time due to poor weather, natural or man‐made disasters, or a combination of any other factors. This work aims to propose a design framework that addresses the facility and link failures explicitly by accounting for their impact on a network's performance measures of efficiency and robustness. Design/methodology/approach The study incorporated a robustness metric for evaluating the resiliency of supply chains in the case of a network disruption. This robustness metric is based on expected losses incurred due to network failures. It defines efficiency and robustness in terms of operational cost and expected disruption cost (EDC), respectively. The EDC is defined in terms of loss of opportunity cost incurred due to not meeting demand on time after a disruption has occurred. The study used a scenario planning approach and formulated a mixed integer linear program model with the objective of maximizing both efficiency and robustness. It also evaluates the trade‐offs between efficiency and robustness. Findings The resulting supply chain is much more reliable in the long term since we have shown that a significant amount of robustness can be built into the system without compromising a lot on efficiency. Originality/value This work demonstrates a methodology which incorporates such disaster scenarios into the design of a supply chain network. This leads to a more reliable supply chain which would lead to higher profitability and lower disruption rates.
Publication Year: 2011
Publication Date: 2011-07-12
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 70
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