A flexible robust model for blood supply chain network design problem

Khalilpourazari, Soheyl; Doulabi, Hossein Hashemi

doi:10.1007/s10479-022-04673-9

Cited by 27 publications

(18 citation statements)

References 39 publications

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“…After applying the equivalent auxiliary crisp model, the two proposed approaches discussed previously, including TH and GMMT, have been utilized to solve the model of this study (Goudarzi et al, 2022 ; Khalilpourazari & Hashemi Doulabi, 2022 ). First, the steps of the TH method are as follows: Step 1: Determine the distribution of each fuzzy parameter with the most pessimistic, the most possible, and the most optimistic values.…”

Section: Solution Methodologymentioning

confidence: 99%

“…While and display the relative importance of ith objective function and compensation coefficient. is the original problem converted into a crisp model (Hosseini Dehshiri et al, 2022 ; Khalilpourazari & Hashemi Doulabi, 2022 ). Also, is determined by DMs based on their preferences given to each objective function.…”

Section: Solution Methodologymentioning

confidence: 99%

“… Each period is one day (Arani et al, 2020 ). Capacity is limited at each BFC, NBB, Hospital, and BDC level (Khalilpourazari & Hashemi Doulabi, 2022 ; Shirazi et al, 2021 ). The blood demand and supply are considered fuzzy numbers (Attari & Jami, 2018 ; Babaee Tirkolaee & Aydın, 2021 ).…”

Section: Problem Definitionmentioning

confidence: 99%

“…Capacity is limited at each BFC, NBB, Hospital, and BDC level (Khalilpourazari & Hashemi Doulabi, 2022 ; Shirazi et al, 2021 ).…”

Section: Problem Definitionmentioning

confidence: 99%

“…A growing concern regarding an efficient CLBSCN is two-fold; first, the total costs of every supply chain should be minimized (Billal et al, 2022 ; Dehghani et al, 2021 ; Ebrahimi et al, 2022 ; Ghahremani-Nahr et al, 2022 ; Khalilpourazari & Hashemi Doulabi, 2022 ; Zhou et al, 2021 ). Second, the service level of the patients should be maximized.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Robust possibilistic programming to design a closed-loop blood supply chain network considering service-level maximization and lateral resupply

et al. 2022

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Reconfiguring the structure of the supply chain network is one of the most strategic and vital decisions in designing a supply chain network. In this study, a Closed-Loop Blood Supply Chain Network (CLBSCN) considering blood group compatibility, ABO-Rh(D), and blood product shelf life has been studied to determine the best strategic and tactical decisions simultaneously considering lateral resupply/transshipment and service-level maximization. Several vital parameters, including supply and demand, are considered fuzzy numbers to approximate reality due to the nature of the world. Furthermore, two crucial factors include ABO-Rh(D) and blood product shelf life considered, while the concept of lateral resupply governs the interconnections of hospitals’ excess blood units. We propose a fuzzy multi-objective Mixed-Integer Non-Linear Programming (MINLP) model to consider two critical objective functions: minimizing the total costs of the network and maximizing the minimum service level to the patients at each Hospital. The fuzzy multi-objective MINLP model is converted to a deterministic multi-objective model using the equivalent auxiliary crisp model to deal with uncertainty. Then, by utilizing two interactive fuzzy solution approaches, the results have been compared based on a real case study to suggest the best solution for the proposed model. Also, we conduct sensitivity analysis on essential parameters such as demand, supply, and capacity to understand how these parameter variations impact two proposed objective functions. Then, the proposed model is tested on a real case study for model validation. The results confirmed that considering the lateral resupply could significantly save the costs of the designed network by a total of $343,000. Interestingly, maximizing the minimum service level at hospitals increased the service level from 58% to 68%.

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Section: Solution Methodologymentioning

confidence: 99%

Section: Solution Methodologymentioning

confidence: 99%

Section: Problem Definitionmentioning

confidence: 99%

“…Capacity is limited at each BFC, NBB, Hospital, and BDC level (Khalilpourazari & Hashemi Doulabi, 2022 ; Shirazi et al, 2021 ).…”

Section: Problem Definitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robust possibilistic programming to design a closed-loop blood supply chain network considering service-level maximization and lateral resupply

et al. 2022

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A two‐stage adaptive robust model for designing a reliable blood supply chain network with disruption considerations in disaster situations

Qing,

Yin,

Wang

et al. 2024

Naval Research Logistics

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We consider multi‐period blood supply chain network design in disaster situations that involve blood donor groups, permanent and temporary blood collection facilities, blood banks, and hospitals. We use a discrete scenario set to model the uncertain blood supply and demand, and the unforeseeable disruptions in permanent blood collection facilities, blood banks, and road links arising from a disaster, where instead of complete failure, disrupted permanent blood collection facilities and blood blanks may only lose part of their capacities. To design a reliable blood supply network to mitigate the possible disruptions, we present a two‐stage adaptive robust model that integrates the location, inventory, and allocation decisions incorporating a blood sharing strategy, where blood can be delivered from a disrupted/non‐disrupted blood bank to disrupted blood banks to enhance the flexibility of the relief network. For this novel problem, we devise an exact algorithm that integrates column‐and‐constraint generation and Benders decomposition and introduce several non‐trivial acceleration techniques to speed up the solution generation process. We conduct extensive numerical studies on random data sets to evaluate the algorithmic performance. We also conduct a case study in Tehran to demonstrate its real‐life applicability and examine the impacts of key model parameters on the solutions. The numerical results verify the benefits of our model over typical benchmarks, that is, deterministic and stochastic models, and the superiority of our solution algorithm over the CPLEX solver and two well‐known solution approaches, that is, column‐and‐constraint generation and Benders decomposition. Finally, based on the numerical results, we derive managerial insights from the analytical findings.

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An overview of weighted goal programming: a multi-objective transportation problem with some fresh viewpoints

Gütmen

Roy

Weber

2023

Cent Eur J Oper Res

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A flexible robust model for blood supply chain network design problem

Cited by 27 publications

References 39 publications

Robust possibilistic programming to design a closed-loop blood supply chain network considering service-level maximization and lateral resupply

Robust possibilistic programming to design a closed-loop blood supply chain network considering service-level maximization and lateral resupply

A two‐stage adaptive robust model for designing a reliable blood supply chain network with disruption considerations in disaster situations

An overview of weighted goal programming: a multi-objective transportation problem with some fresh viewpoints

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