A socio-economic optimization model for blood supply chain network design during the COVID-19 pandemic: An interactive possibilistic programming approach for a real case study

Tirkolaee, Erfan Babaee; Golpîra, Hêriş; Javanmardan, Ahvan; Maihami, Reza

doi:10.1016/j.seps.2022.101439

Cited by 40 publications

(19 citation statements)

References 55 publications

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“…In this regard, the following recommendations are given to extend the current study: i. Applying other techniques to handle and analyze uncertainty such as stochastic optimal control (Savku and Weber 2018;Pervin et al 2018;Tirkolaee et al 2022c), possibilistic programming (Tirkolaee et al 2022b), and regression models (Özmen et al 2017, 2018), which can be compared to the proposed method, ii. Expanding the supply chain network by including more levels such as suppliers and retailers and with respect the target industry (Paksoy et al 2013;Tirkolaee et al 2021a), iii.…”

Section: Discussionmentioning

confidence: 99%

A branch and efficiency algorithm to design a sustainable two-echelon supply chain network considering traffic congestion and uncertainty

Babaei

Khedmati

Jokar

2022

Environ Sci Pollut Res

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This work aims to design a sustainable two-echelon supply chain not only based on the widely used cost perspective, but also based on the efficient use and preservation of limited resources. For this purpose, a branch and efficiency (B&E) algorithm is developed, which includes an optimization model and an evaluation model. The proposed tri-objective optimization model simultaneously minimizes the total cost of the supply chain, maximizes the sustainability score, and minimizes inequity among customers. The solutions obtained from the optimization model are then evaluated by extended data envelopment analysis (EDEA) models based on common criteria (i.e., cost and service) and traffic congestion criterion. To take into account real-world conditions, parameters related to labor and demand are assumed under uncertainty. Since the presented models consist of more than one objective function, fuzzy goal programming (FGP) method is utilized to tread the multiobjectiveness. The obtained results from tackling a case study problem demonstrate that considering sustainability issues can positively affect both the economic and social aspects of the problem. Furthermore, the developed B&E algorithm is able to reduce costs in each iteration; this is what supply chain managers are interested in. On the other hand, this algorithm can provide more services to applicants compared to one of the competing algorithms.

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Section: Discussionmentioning

confidence: 99%

A branch and efficiency algorithm to design a sustainable two-echelon supply chain network considering traffic congestion and uncertainty

Babaei

Khedmati

Jokar

2022

Environ Sci Pollut Res

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“…This will further increase unit carbon emission reduction, market demand and environmental pollution reduction. Given that manufacturing is the main economic sector and the basis of economic growth (Tirkolaee et al, 2022), technological progress and investment will bring economic growth (Iqbal et al, 2022), and environmental pollution will harm economic growth (Murshed, 2022), so it is reasonable to state that embedded service in supply chains can maintain economic growth.…”

Section: Figure 10mentioning

confidence: 99%

Will the embedded service in supply chains play a role in lowering manufacturer’s carbon emission and maintaining economic growth?

Shi

Chen

Yu³

et al. 2023

Front. Environ. Sci.

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Introduction: The carbon cap and trade mechanism (CCTM) is forcing companies to reduce carbon emissions. Due to financial and technical constraints, manufacturers responsible for recycling and remanufacturing begin to seek embedded services from energy service companies (ESCOs), marking the emergence of embedded low-carbon service supply chains. The purpose of this paper is to explore the role of embedded low-carbon service in supply chains in lowering manufacturer’s carbon emissions and maintaining economic growth.Methods: In this paper, a decision model for risk-averse closed-loop supply chain for embedded low-carbon service in uncertain markets is built by using the Stackelberg theory and mean-variance (MV) approach. Equilibrium decisions, the manufacturer’s expected utility growth, and total carbon emission reduction are obtained. Sensitivity analysis is performed for the main parameters.Results: The results indicate that only when the manufacturer’s risk aversion level and consumers’ low-carbon preference are within the range of 0.35–0.9, can the manufacturer bring in embedded low-carbon service by cooperating with an ESCO through revenue-sharing contracts. When there is a higher carbon price, embedded low-carbon service can further increase the manufacturer’s expected utility, maintain economic growth and reduce carbon emissions.Discussion: Embedded low-carbon service in supply chains can play a role in lowering manufacturers’ carbon emissions and maintaining economic growth when the manufacturer’s risk aversion level, carbon price, and consumers’ low-carbon preference are high. Theoretically, this study combines closed-loop supply chains (CLSCs) and embedded low-carbon services, enriching supply chain theories. In addition, the findings provide managerial insights for manufacturers, ESCOs, and governments.

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“…Recently, many studies have focused on the impact assessment of COVID-19 on safety and healthcare (e.g., [7] , [8] ), logistics and supply chains (e.g., [9] , [10] , [11] , [12] ), and on COVID-19 risk assessment [13] , [14] , [15] .…”

Section: Introductionmentioning

confidence: 99%

Predicting and explaining absenteeism risk in hospital patients before and during COVID-19

Borges

Carvalho

Maia

et al. 2023

Socio-Economic Planning Sciences

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A socio-economic optimization model for blood supply chain network design during the COVID-19 pandemic: An interactive possibilistic programming approach for a real case study

Cited by 40 publications

References 55 publications

A branch and efficiency algorithm to design a sustainable two-echelon supply chain network considering traffic congestion and uncertainty

A branch and efficiency algorithm to design a sustainable two-echelon supply chain network considering traffic congestion and uncertainty

Will the embedded service in supply chains play a role in lowering manufacturer’s carbon emission and maintaining economic growth?

Predicting and explaining absenteeism risk in hospital patients before and during COVID-19

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