Reliable blood supply chain network design with facility disruption: A real-world application

Haghjoo, Nazanin; Tavakkoli–Moghaddam, Reza; Shahmoradi-Moghadam, Hani; Rahimi, Yaser

doi:10.1016/j.engappai.2020.103493

Cited by 85 publications

(31 citation statements)

References 36 publications

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“…Among the differences between our study and that of Haghjoo et al. [1] , we can point out plasma inventory control, multi-commodity model, and plasma demand estimation using simulation. Rajendran and Ravindran [36] proposed a stochastic model for managing platelet inventory in blood supply chain.…”

Section: Literature Reviewmentioning

confidence: 63%

“…Haghjoo et al. [1] designed a reliable blood supply chain. A multi-period robust mathematical model was presented at the time of disaster.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In addition to medical treatment, many diseases require humanitarian help such as blood supply. Blood or its components are vitally essential for many patients such as thalassemia suffering individuals, car accident victims and those seriously suffering from Coronavirus Disease 2019 (COVID-19) [1] . The recently discovered coronavirus causes an infectious disease called COVID-19 [2] .…”

Section: Introductionmentioning

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: 63%

“…Haghjoo et al. [1] designed a reliable blood supply chain. A multi-period robust mathematical model was presented at the time of disaster.…”

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

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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“…The changes in the supply chain after the disaster and the optimum strategies to be followed are examined in this sub-study area. Jabbarzadeh et al ( 2014 ), Fahimnia et al ( 2017 ), Samani et al ( 2018 ), Glasgow et al ( 2018 ), Diabat et al ( 2019 ), Fazli-Khalaf et al ( 2019 ), Sharma et al ( 2019 ), Salehi et al ( 2019 ), Rahmani ( 2019 ), Khalilpourazari and Khamseh ( 2019 ), Haghjoo et al ( 2020 ), Hamdan and Diabat ( 2020a , b ), Wang and Chen ( 2020 ) are current examples on this topic.…”

Section: Literature Surveymentioning

confidence: 99%

Re-design of a blood supply chain organization with mobile units

2021

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This research analyses the re-organization of a blood supply chain organization. Blood supply chain network design is a hard problem. Uncertainties of the blood supply and demand, perishability of blood over time and compatibility of blood types are some factors that make the problem difficult. This paper presents a novel multi-objective mixed-integer location-allocation model for a blood supply chain design problem. Unlike many studies on blood supply chain design in the literature, supply chain network consisting of mobile and permanent units is planned together effectively with our mixed-integer programming model. Multi-objective structure of the model minimizes distances between the blood supply chain elements and the length of the mobile unit routes. The objectives are prioritized by experts using the Analytical Hierarchical Process. Finally, the model is implemented on a real life case study using real data from the Eastern Anatolia region of Turkey for various supply demand scenarios. The solutions offered by the model are compared with the current situation in the region. It is shown that the proposed model gives at least %25 more effective solutions. Moreover, sensitivity analysis on the budget constraint is conducted, and robustness of the model is empirically illustrated.

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“…First, the efficiency of potential suppliers is determined by fuzzy DEA, and then a two-stage possibilistic-stochastic programming model is created to select a supplier, and the results are examined in a pharmaceutical company for the application of the presented model. In the health supply chain section, Haghjoo et al [54] proposed a dynamic robust location-allocation model to solve the disruption in the blood supply to hospitals and designed a scenario-based robust approach for the inherent uncertainty of the problem. Besides, to solve the large-scale problems, they proposed two metaheuristic algorithms, namely, the self-adaptive imperialist competitive and invasive weed optimization.…”

Section: Facility Location Problems Under Disruptionsmentioning

confidence: 99%

Five-Echelon Multiobjective Health Services Supply Chain Modeling under Disruption

Gargari

Sayad

Mashhadi

et al. 2021

Mathematical Problems in Engineering

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Medicine unreliability problem is taken into consideration as one of the most important issues in health supply chain management. This research is associated with the development of a multiobjective optimization problem for the selection of suppliers and distributors. To achieve the purposes, the optimal quota allocation is determined with respect to disruption of suppliers in a five-echelon supply chain network and consideration of the distributor centers as a hub location-allocation mode. The objective of the optimization model is involved in simultaneous minimization of transactions costs dealing with suppliers, expected purchasing costs from suppliers, expected percentages of delayed and returned products in each distributor, as well as transportation cost in each echelon and fixed cost for distributor centers, and finally maximization of the expected scores for suppliers and high priority of product customers. The optimization problem is formulated as a mixed-integer nonlinear programming model. The proposed optimization model is utilized to investigate a numerical case study for asthma-specific medicines. The analyzing procedure is conducted based on the collected real data from Cobel Darou pharmaceutical company in 2019. Furthermore, a fuzzy multichoice goal programming model is considered to solve the proposed optimization model by R optimization solver. The numerical results confirmed the authenticity of the model.

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Reliable blood supply chain network design with facility disruption: A real-world application

Cited by 85 publications

References 36 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

Re-design of a blood supply chain organization with mobile units

Five-Echelon Multiobjective Health Services Supply Chain Modeling under Disruption

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