2017
DOI: 10.1016/j.cie.2017.07.009
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Supply chain design considering correlated failures and inspection in pharmaceutical and food supply chains

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Cited by 20 publications
(10 citation statements)
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References 25 publications
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“…Although details differ across studies, most of them share a common set of outcomes and managerial insights, such as joint optimization of SC capacities and recovery capabilities for new and existing SCs; trade-offs between investments in increased recovery capability and redundant capacity provision; decision-making support on safety stock management, reconfiguration of production and inventory plans after disruptions, and recovery scheduling ( Ivanov et al, 2015 ; Sinha et al, 2020 ; Goldbeck et al, 2020). As the most desirable outcome, process level analysis seeks to identify and test resilient SC designs to sustain disruptions, which range from optimistic and pessimistic scenarios ( Ivanov et al, 2014a ), probability-based disruptions ( Pariazar et al, 2017 ) to worst-case scenarios in robust optimization ( Zhao and Freeman, 2019 ; Özçelik et al, 2020 ). In some settings, the authors solve inverse problems and search for the elements in SC structures that should be strengthened to withstand disruption propagation ( Liberatore et al, 2012 ; Pavlov et al, 2013).…”
Section: Theories Major Outcomes and Managerial Insightsmentioning
confidence: 99%
See 1 more Smart Citation
“…Although details differ across studies, most of them share a common set of outcomes and managerial insights, such as joint optimization of SC capacities and recovery capabilities for new and existing SCs; trade-offs between investments in increased recovery capability and redundant capacity provision; decision-making support on safety stock management, reconfiguration of production and inventory plans after disruptions, and recovery scheduling ( Ivanov et al, 2015 ; Sinha et al, 2020 ; Goldbeck et al, 2020). As the most desirable outcome, process level analysis seeks to identify and test resilient SC designs to sustain disruptions, which range from optimistic and pessimistic scenarios ( Ivanov et al, 2014a ), probability-based disruptions ( Pariazar et al, 2017 ) to worst-case scenarios in robust optimization ( Zhao and Freeman, 2019 ; Özçelik et al, 2020 ). In some settings, the authors solve inverse problems and search for the elements in SC structures that should be strengthened to withstand disruption propagation ( Liberatore et al, 2012 ; Pavlov et al, 2013).…”
Section: Theories Major Outcomes and Managerial Insightsmentioning
confidence: 99%
“…Amid the control and mitigation stage, SCs must adapt to a “new normal” and start preparing for recovery. For example, OR models can help to identify balanced levels of capacity utilization and production rates at different firms in the SC to achieve maximum possible performance ( Ivanov et al, 2016 ; Pariazar et al, 2017 ; Goldbeck et al 2020). It is now highly relevant to the COVID-19 pandemic since SCs are misbalanced, which makes it difficult to decide at which level of capacity firms should start and then scale during a subsequent recovery.…”
Section: Directions For Managerial Applications and Future Research Imentioning
confidence: 99%
“…In 2017, Pariazar and his co-authors developed a two-step stochastic programming model to explore trade-offs between costs and risk factors to establish a food supply chain. They also present a number of calculation results in their article [8].…”
Section: Proportion Of Abstract In Publicationsmentioning
confidence: 99%
“…The proposed model which integrates the quantity discount and coordination model for addressing supplier selection issue, has been solved by the particle swarm optimization algorithm and scatter search algorithm. The supplier selection problem in the forward distribution network addressed by Pariazar et al [27]. In the proposed model, supplier failures and inspection as supplier selection were considered with other supply chain network decision in the uncertain environment.…”
Section: Literature Reviewmentioning
confidence: 99%