Closed-loop supply chain network design and modelling under risks and demand uncertainty: an integrated robust optimization approach

2018 ◽  
Vol 290 (1-2) ◽  
pp. 837-864 ◽  
Author(s):  
Surya Prakash ◽  
Sameer Kumar ◽  
Gunjan Soni ◽  
Vipul Jain ◽  
Ajay Pal Singh Rathore
Keyword(s):  
Supply Chain ◽  
Robust Optimization ◽  
Network Design ◽  
Demand Uncertainty ◽  
Closed Loop ◽  
Optimization Approach ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Closed Loop Supply Chain

Robust Hazardous Materials Closed-Loop Supply Chain Network Design with Emergency Response Teams Location

2021 ◽  
pp. 036119812199207
Author(s):  
Nasrin Mohabbati-Kalejahi ◽  
Alexander Vinel
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Emergency Response ◽  
Closed Loop ◽  
Hazardous Materials ◽  
Risk Exposure ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Closed Loop Supply Chain

Hazardous materials (hazmat) storage and transportation pose threats to people’s safety and the environment, which creates a need for governments and local authorities to regulate such shipments. This paper proposes a novel mathematical model for what is termed the hazmat closed-loop supply chain network design problem. The model, which can be viewed as a way to combine several directions previously considered in the literature, includes two echelons in the forward direction (production and distribution centers), three echelons in the backward direction (collection, recovery, and disposal centers), and emergency response team positioning. The two objectives of minimizing the strategic, tactical, and operational costs as well as the risk exposure on road networks are considered in this model. Since the forward flow of hazmat is directly related to the reverse flow, and since hazmat accidents can occur at all stages of the lifecycle (storage, shipment, loading, and unloading, etc.), it is argued that such a unified framework is essential. A robust framework is also presented to hedge the optimization model in case of demand and return uncertainty. The performance of both models is evaluated based on a standard dataset from Albany, NY. Considering the trade-offs between cost and risk, the results demonstrate the design of efficient hazmat closed-loop supply chain networks where the risk exposure can be reduced significantly by employing the proposed models.

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