A deterministic inventory model in reverse supply chain

Mohapatra, Sasmita; Behera, Ajay Kumar; Mahapatra, Rabindra Narayan; Das, Harish Chandra

doi:10.1108/jm2-03-2019-0076

Cited by 3 publications

(5 citation statements)

References 33 publications

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“…The optimal lot size for Qp and Qr and Tp, and Tr for the above ideal system is formulated based on the original work by Mohapatra et al [21]as follows:…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…They designed a stochastic dynamic programming problem with different alternatives so that total expected costs for inventory holding, shortage and purchasing can be minimised. The study by Mohapatra et al [21] is concerned with inventory control for a remanufacturing system in which stationary demand is met by both remanufactured and newly purchased products. The model assumes that customer return products are remanufactured at a constant rate and the economic order quantity (EOQ) for manufactured and remanufactured items is computed at the same time.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Lot-Sizing Decisions for a Remanufacturing Production System under Spare Parts Supply Uncertainty

Ropi¹,

Hishamuddin²,

Wahab³

et al. 2023

Preprint

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Remanufacturing is a way for product recovery initiative and maintaining sufficient production flow to satisfy customer demand through circular economy. Recently, manufacturers have been progressively incorporating remanufacturing processes, making their supply chain vulnerable to disruptions. Among the disruptions that usually occur is the shortage in spare parts supply, which causes unexpected delay in production and possible loss of sales. In the face of potential disruption, it is essential for remanufacturing facilities to manage their supply chains in an optimum manner as to decrease the adverse impact of disruptions to their business. In this study, a two-stage production-inventory system is analysed by developing a cost-minimisation model focusing on the recovery schedule after a disruption occurrence in sourcing spare parts for a remanufacturer’s production cycle. The developed model was solved using the branch and bound algorithm. Through numerical experiments, the results indicate that the optimal recovery schedule and the number of recovery cycles are significantly dependant on disruption time, lost sales and backorder costs. Moreover, a sensitivity analysis shows that the lost sales option seems to be more effective than the backorder option in optimising the system’s overall cost. The proposed model could assist managers in deciding the optimal production strategy while providing interesting managerial insights into vital spare parts recovery issues when disruption strikes.

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“…The optimal lot size for Qp and Qr and Tp, and Tr for the above ideal system is formulated based on the original work by Mohapatra et al [21]as follows:…”

Section: Mathematical Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Lot-Sizing Decisions for a Remanufacturing Production System under Spare Parts Supply Uncertainty

Ropi¹,

Hishamuddin²,

Wahab³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The optimal lot size for Q p and Q r and T p , and T r for the above ideal system is formulated on the basis of the original work by Mohapatra et al [44] as follows:…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…One of the model's novelties was its focus on the product modules derived from the bill of materials; given this feature, the model can define the spare parts market. The study by Mohapatra et al [44] is concerned with inventory control for a remanufacturing system in which stationary demand is met by remanufactured and newly purchased products. The model assumes that customer return products are remanufactured at a constant rate, and the economic order quantity for manufactured and remanufactured items is computed simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Optimal Lot-Sizing Decisions for a Remanufacturing Production System under Spare Parts Supply Disruption

Mat Ropi,

Hishamuddin,

Wahab

et al. 2023

Mathematics

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Remanufacturing is one of the ways forward for product recovery initiatives and for maintaining sufficient production flow to satisfy customer demand by providing high-quality goods with a combination of new and return parts through a circular economy. Recently, manufacturers have been progressively incorporating remanufacturing processes, making their supply chains vulnerable to disruptions. One of the main disruptions that occurs in remanufacturing systems is the shortage of spare parts supply, which results in unexpected delays in the remanufacturing process and could eventually result in a possible loss of sales. In the event of such potential disruptions, remanufacturing facilities must manage their supply chains in an effective and optimal manner such that the negative impact of disruptions to their business can be minimised. In this study, a two-stage production–inventory system was analysed by developing a cost-minimisation model that focuses on the recovery schedule after the occurrence of a disruption in sourcing spare parts for a remanufacturer’s production cycle. The developed model was solved using the branch-and-bound algorithm, where the experimental results demonstrated that the model provides effective solutions. Through numerical experiments, results indicated that the optimal recovery schedule and the number of recovery cycles are considerably dependent on the disruption time, lost sales and backorder costs. A sensitivity analysis showed that the lost sales option seems to be more effective than the backorder sales option in optimising the system’s overall cost due to unmet demand, which becomes lost sales when serviceable items are reduced, thereby shortening recovery time. Furthermore, a case study revealed that a manufacturer’s response to disruption is highly influenced by the spare part costs and overall recovery costs as well as the supplier’s readiness level. The proposed model could assist managers in deciding the optimal production strategy whilst providing interesting managerial insights into vital spare parts recovery issues when disruption strikes.

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“… Afshari et al, 2016 ; Aydin, 2020 ; Ayvaz et al, 2015 ; Bertsimas and Sim, 2004 ; Chakraborty et al, 2018 ; De Rosa et al, 2013 ; Demirel et al, 2016 ; Doan et al, 2018 ; Fang et al, 2011 ; Feitó-Cespón et al, 2017 ; Ghadge et al, 2016 ; Gu and Gao, 2012 ; Hamdan and Diabat, 2020 ; Hamidieh et al, 2017 ; Hatefi and Jolai, 2014 ; Hatefi et al, 2015 ; Hatefi et al, 2016 ; Heydari and Ghasemi, 2018 ; Heydari et al, 2018 ; Hosseini-Motlagh et al, 2019 ; Hosseini-Motlagh et al, 2020 ; Hosseini and Sarder, 2019 ; Hosseini and Ivanov, 2019 ; Hosseini et al, 2019a ; Hosseini et al, 2019b ; Ivanov et al, 2014a ; Ivanov et al, 2014b ; Ivanov et al, 2016 ; Ivanov et al, 2017 ; Jabbarzadeh et al, 2014 ; Jain et al, 2017 ; John et al, 2018 ; Kinra et al, 2019 ; Liao, 2018 ; Mohapatra et al, 2019 ; Niknejad and Petrovic, 2014 ; Pavlov et al, 2019 ; Pishvaee et al, 2011 ; Phuc et al, 2017 ; Qiaolun and Tiegang, 2012 ; Qiaolun and Tiegang, 2013 ; Ren et al, 2020 ; Sawik, 2017 ; Setak et al, 2019 ; Shuang et al, 2019 ; Suryawanshi and Dutta, 2019 ; Tosarkani and Amin, 2019 ; Tucker et al, 2020 ; Yu and Solvang, 2017 ; Zhang et al, 2018 ; Zhao et al, 2018 .…”

Section: Uncited Referencesunclassified

Ensuring sustainability in the reverse supply chain in case of the ripple effect: A two-stage stochastic optimization model

Yılmaz

Özçelik

Yeni

2021

Journal of Cleaner Production

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The devastating impact of the ripple effect increases the importance of the reverse supply chain (RSC) design to ensure sustainability in the long-term. That being the case, in this study, a two-stage stochastic mixed-integer optimization model is proposed to design an RSC network under uncertainty sourcing from the ripple effect (i.e. external side of RSC) by considering the environmental and economic dimensions of sustainability. The environmental and economic disruptions of the ripple effect are represented by the increase in the carbon emission levels and the distance of roads, and the decrease in the capacity of facilities, respectively. Accordingly, a set of scenarios is considered based on the disruption levels (low- and high-impact) in case of the ripple effect. Furthermore, an -reliability constraint is integrated into the model to further analyze the occurrence of scenarios. The model allows us to make integrated operational and strategic decisions by placing an emphasis on the carbon emission levels (i.e. environmental dimension) and the total cost (i.e. economic dimension). To obtain some remarkable insights, the proposed model is validated through computational experiments based on data extracted from a real case. The computational results show that the ripple effect increases the emission level and total cost up to 40%. For this reason, it suggested that the regulations regarding WEEE (Waste Electrical and Electronic Equipment) should be prepared by considering sustainability in the entire RSC network. Besides, it is realized that the centralized distribution strategy leads to a more resilient RSC network design.

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A deterministic inventory model in reverse supply chain

Cited by 3 publications

References 33 publications

Optimal Lot-Sizing Decisions for a Remanufacturing Production System under Spare Parts Supply Uncertainty

Optimal Lot-Sizing Decisions for a Remanufacturing Production System under Spare Parts Supply Uncertainty

Optimal Lot-Sizing Decisions for a Remanufacturing Production System under Spare Parts Supply Disruption

Ensuring sustainability in the reverse supply chain in case of the ripple effect: A two-stage stochastic optimization model

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