Robust and stable flexible blood supply chain network design under motivational initiatives

Hosseini‐Motlagh, Seyyed‐Mahdi; Samani, Mohammad Reza Ghatreh; Cheraghi, Sara

doi:10.1016/j.seps.2019.07.001

Cited by 49 publications

(30 citation statements)

References 47 publications

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“…Compared with the research done by Hosseini-Motlagh et al. [27] , the advantages of our study are considering different blood types and their substitution priority, and allocating the centers to demand points and examining the flow among the centers. In addition, Hosseini-Motlagh et al.…”

Section: Literature Reviewmentioning

confidence: 98%

“…Hosseini-Motlagh et al. [27] presented a robust mathematical model for managing blood supply chain under uncertainty, the study whose contribution was undertaking motivational initiatives of governments to encourage donors to donate blood. Locating blood distribution centers accompanied with their allocating capacity was one of the objectives of their research.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In addition, Hosseini-Motlagh et al. [27] considered deterministic demand, while in our research, demand is estimated by a simulation approach. Goodarzian et al.…”

Section: Literature Reviewmentioning

confidence: 99%

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A stochastic bi-objective simulation–optimization model for plasma supply chain in case of COVID-19 outbreak

Shirazi

Kia

Ghasemi

2021

Applied Soft Computing

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As of March 24, 2020, the Food and Drug Administration (FDA) authorized to bleed the newly recovered from Coronavirus Disease 2019 (COVID-19), i.e., the ones whose lives were at risk, separate Plasma from their blood and inject it to COVID-19 patients. In many cases, as observed the plasma antibodies have cured the disease. Therefore, a four-echelon supply chain has been designed in this study to locate the blood collection centers, to find out how the collection centers are allocated to the temporary or permanent plasma-processing facilities, how the temporary facilities are allocated to the permanent ones, along with determining the allocation of the temporary and permanent facilities to hospitals. A simulation approach has been employed to investigate the structure of COVID-19 outbreak and to simulate the quantity of plasma demand. The proposed bi-objective model has been solved in small and medium scales using -constraint method, Strength Pareto Evolutionary Algorithm II (SPEA-II), Non-dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Grey Wolf Optimizer (MOGWO) and Multi Objective Invasive Weed Optimization algorithm (MOIWO) approaches. One of the novelties of this research is to study the system dynamic structure of COVID-19’s prevalence so that to estimate the required plasma level by simulation. Besides, this paper has focused on blood substitutability which is becoming increasingly important for timely access to blood. Due to shorter computational time and higher solution quality, MOIWO is selected to solve the proposed model for a large-scale case study in Iran. The achieved results indicated that as the plasma demand increases, the amount of total system costs and flow time rise, too. The proposed simulation model has also been able to calculate the required plasma demand with 95% confidence interval.

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Section: Literature Reviewmentioning

confidence: 98%

Section: Literature Reviewmentioning

confidence: 99%

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A stochastic bi-objective simulation–optimization model for plasma supply chain in case of COVID-19 outbreak

Shirazi

Kia

Ghasemi

2021

Applied Soft Computing

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“…Although the above mentioned studies tackle interesting and significant issues, there is a clear dearth of modeling research on blood donor behavior which is a critical and unique part of supply chain management of this life-saving product, which cannot be produced but must be donated. Hosseini-Motlagh et al [ 75 ] developed a novel mixed possibilistic-stochastic flexible robust model that takes into consideration the critical role played by blood donors. Their study included motivational initiatives aimed at encouraging blood donors in order to maintain a sufficient blood supply.…”

Section: Literature Reviewmentioning

confidence: 99%

A Multiclass, Multiproduct Covid-19 Convalescent Plasma Donor Equilibrium Model

Nagurney

Dutta

2021

SN Oper. Res. Forum

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“…Referring to the research of Hosseini-Motlagh et al ( 2020 ) and based on the knowledge of MOHME experts, this study considers three inputs, namely traffic, pollution, and natural disasters incidence, and three outputs, namely population density, appropriate workplace, and skilled staff. According to the judgment of experts, these criteria are those with utmost importance and significant influence among the others in finding the best candidate places for health facilities and hence have been included in this paper:…”

Section: The Casementioning

confidence: 99%

An integrated socially responsible-efficient approach toward health service network design

et al. 2021

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Despite the fact that medical responses are crucial for saving precious lives during any humanitarian crisis (e.g., the COVID-19 pandemic), healthcare infrastructure in many communities are partially covered or are not covered yet. In order to strengthen the health system response to such crisis, especially in low-to middle-income communities, this paper extends a novel multi-objective model for designing a health service network under uncertainty which simultaneously considers efficiency, social responsibility, and network cost. For efficiency, a modified data envelopment analysis model is introduced and inserted into the proposed model to decrease the inefficiency of healthcare facilities belonging to the different tiers of the health system. For social responsibility, two measures of job creation and balanced development are incorporated into the extended model. This is not only considered to cope with the increased numbers of patients and disaster victims to healthcare facilities but also to deal with the challenge of the economy and the livelihoods of people during the crisis. Moreover, a novel mixed possibilistic-flexible robust programming (MPFRP) approach is developed to protect the considered network against uncertainty. To show the applicability of the extended model, a real-world case study is presented. The results reveal that contrary to fuzzy programming models, the MPFRP performs well in terms of social responsibility (72%), cost (8%), and efficiency (28%) and is able to make a trade-off between these three measures. In this study, the resilience level of the designed network is not addressed while disregarding any short-term stoppage owing to internal or external sources of disruption in designing may bring about a considerable loss.

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Robust and stable flexible blood supply chain network design under motivational initiatives

Cited by 49 publications

References 47 publications

A stochastic bi-objective simulation–optimization model for plasma supply chain in case of COVID-19 outbreak

A stochastic bi-objective simulation–optimization model for plasma supply chain in case of COVID-19 outbreak

A Multiclass, Multiproduct Covid-19 Convalescent Plasma Donor Equilibrium Model

An integrated socially responsible-efficient approach toward health service network design

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