scholarly journals A Trade-off Analysis of Economic and Environmental Aspects of a Disruption Based Closed-Loop Supply Chain Network

2020 ◽  
Vol 12 (17) ◽  
pp. 7056
Author(s):  
Abdul Salam Khan ◽  
Catalin Iulian Pruncu ◽  
Razaullah Khan ◽  
Khawar Naeem ◽  
Abdul Ghaffar ◽  
...  

Closed-loop supply chain networks are gaining research popularity due to environmental, economic and social concerns. Such networks are primarily designed to overcome carbon footprints and to retrieve end of life products from customers. This study considers a multi echelon closed-loop supply chain in the presence of machine disruption. A multi-objective model is presented to optimize the total cost, the total time and emissions in a closed-loop supply chain network. The aim is to analyze the trade-off between the objectives of cost, time, and emissions and how these decisions are impacted by the selection of different available machines. A number of solution approaches are tested on a case study from the tire industry. The results suggest the improved performance of the hybrid heuristic and the importance of controlling disruption in a closed-loop supply chain network. Furthermore, there is a trade-off between the different objective functions which can help the decision maker to choose a particular solution according to the preference of an organization. Finally, conclusion and future research avenues are provided.

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Guitao Zhang ◽  
Hao Sun ◽  
Jinsong Hu ◽  
Gengxin Dai

This paper studies a closed-loop supply chain network equilibrium problem in multiperiod planning horizons with consideration of product lifetime and carbon emission constraints. The closed-loop supply chain network consists of suppliers tier, manufacturer tier, retailers tier, and demand markets tier, in which the manufacturers collect used products from the demand markets directly. Product lifetime is introduced to denote the maximum times of manufacturing and remanufacturing, and the relation between adjacent periods is described by inventory transfer. By variational inequalities and complementary theory, the optimal behaviors of all the players are modeled, and, in turn, the governing closed-loop supply chain network equilibrium model is established. The model is solved by modified project contraction algorithm with fixed step. Optimal equilibrium results are computed and analyzed through numerical examples. The impacts of collection rate, remanufacturing conversion rate, product lifetime, and carbon emission cap on equilibrium states are analyzed. Finally, several managerial insights are given to provide decision support for entrepreneurs and government official along with some inspirations for future research.


Logistics ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 20
Author(s):  
Mohsen Tehrani ◽  
Surendra M. Gupta

The ever-increasing concerns of the growth in the volume of waste tires and new strict government legislations to reduce the environmental impact of the end-of-life (EOL) tires have increased interest among companies to design a sustainable and efficient closed-loop supply-chain (CLSC) network. In the real world, the CLSC network design is subject to a variety of uncertainties, such as random and fuzzy (epistemic) uncertainties. Designing a reliable and environmentally cautious CLSC with consideration of risks and the uncertainty of the parameters in the network is necessary for a successful supply-chain network. This study proposes a sustainable and environmentally cautious closed-loop supply-chain network for the tire industry, by considering several recovery options, including retreading, recycling, and energy recovery. This study aims to design and develop a robust multi-objective, multi-product, multi-echelon, multi-cycle, multi-capacity, green closed-loop supply-chain network under hybrid uncertainty. There are two types of uncertainties associated with the parameters in the network. There is an uncertainty associated with the demand, which is expressed in some future scenarios according to the probability of their occurrences, as well as fuzzy-based uncertainty associated with return rates, retreading rates, recycling rates, procurement, and production costs, which are expressed with possibilistic distributions. In order to deal with this hybrid uncertainty, a robust fuzzy stochastic programming approach has been proposed, and the proposed mixed integer programming model is applied to a case study in the tire industry to validate the model. The result indicates the applicability of the proposed model and its efficiency to control the hybrid uncertainties and the risk level in the network.


Author(s):  
Nasrin Mohabbati-Kalejahi ◽  
Alexander Vinel

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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