Designing blood supply chain networks with disruption considerations by a new interval-valued fuzzy mathematical model: M/M/C queueing approach

Eghbali, Shahin; Mousavi, Seyed Meysam; Salimian, Sina

doi:10.1016/j.cie.2023.109260

Cited by 7 publications

(1 citation statement)

References 44 publications

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“…Rezapour et al [42] considered mitigation strategy selection to offset the adverse effect of supplier disruptions on the market share from a single manufacturer perspective in supply chain network planning. Eghbali et al [43] modeled the blood supply network with the objective of minimizing the system's cost and time, considering the facility disruptions, and conducted a case application in a province in the north of Iran. Sensitivity analysis found that increasing the number of transportation modes had an important role in reducing the system's waiting time.…”

Section: Supply Chain Network Design Considering Disruption Riskmentioning

confidence: 99%

A Bi-Objective Optimization Model for a Low-Carbon Supply Chain Network with Risk of Uncertain Disruptions

Wang,

Ji,

Lang

2023

Symmetry

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Disruption risks exacerbate the complexity of low-carbon supply chain network design in an uncertain supply chain environment. Considering the low frequency and non-repeatability of these disruption events makes it impossible to collect data to obtain their probabilities. In this study, supply disruptions were regarded as uncertain events; supply chain uncertain disruption risk is defined and quantified based on the uncertainty theory, in which uncertain disruptions are characterized by the belief degree on account of expert estimation with duality, i.e., symmetry. Optimization models were constructed with the objective of minimizing expected carbon emissions and costs, which optimizes the selection of suppliers with uncertain disruptions, and the assignment of manufacturers and customers. The properties of the model were analyzed, and the models were solved separately using different methods according to different decision criteria. Finally, the validity of the proposed models and algorithm were verified using a real case study of a glass manufacturing company. The findings exhibit promising insights for designing a sustainable and resilient supply chain network in an uncertain environment.

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Section: Supply Chain Network Design Considering Disruption Riskmentioning

confidence: 99%