Integrating bloodmobiles and drones in a post-disaster blood collection problem considering blood groups

Kallaj, Mahsa Rezaei; Kolaee, M. Hasannia; Al-e-hashem, S.M.J. Mirzapour

doi:10.1007/s10479-022-04905-y

Cited by 8 publications

(4 citation statements)

References 28 publications

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“…However, the handling of uncertainties within the context of drone-based blood transportation remains limited. For instance, Rezaei et al [ 43 ] formulated uncertain blood demand as a two-stage stochastic problem, while Hou et al [ 38 ] proposed a data-driven two-stage stochastic optimization model employing the Wasserstein distance to minimize network costs while adhering to flow, capacity, and energy constraints.…”

Section: Literature Reviewmentioning

confidence: 99%

“…However, the handling of uncertainties within the context of drone-based blood transportation remains limited. For instance, Rezaei et al [43] formulated uncertain blood demand as a two-stage PLOS ONE In recent years, the confluence of operations research and logistics expertise has generated an array of drone applications for diverse cargo types. Although the majority of drone delivery literature centers on e-commerce logistics, a substantial body of work has also emerged within emergency and healthcare services, as depicted in Table 1.…”

Section: Literature Reviewmentioning

confidence: 99%

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A hierarchical model for strategic and operational planning in blood transportation with drones

Amirsahami,

Barzinpour,

Pishvaee

2023

PLoS ONE

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Blood transportation is a critical aspect of the healthcare systems, ensuring whole blood and blood products are delivered to patients in a timely and efficient manner. However, transportation of blood and other medical supplies can be challenging, especially in urban areas with limited infrastructure and heavy traffic. Drones have become increasingly important in recent years as a means of delivering medical supplies, including blood, due to their ability to provide fast, reliable, and cost-effective transportation. This study proposes two mathematical programming models in the hierarchical structure to improve decision-making for strategic and operational planning in the blood supply chain network. The limited information available in strategic planning presents risks to the blood supply chain, making it imperative to address uncertainties. To tackle this challenge, a novel approach called Scenario-based Robust Bi-objective Optimization has been proposed. The first model employs this approach to efficiently handle demand uncertainty by simultaneously maximizing the covered demand and minimizing costs. The model is subsequently solved using the augmented ε-constraint method. The second model is a routing-scheduling operational model that aims to minimize the sum of operations time, taking into account time windows for blood collection centers and hospitals. The developed hierarchical model is implemented in a three-level supply chain of Tehran province under three crisis scenarios in different parts. The findings and analysis of this implementation suggest that it is beneficial to set up drone stations in cost-effective and central locations to avoid costly network design. Furthermore, utilizing the minimum number of feasible drones enhances operational time and results in cost savings and increased efficiency. Overall, this study highlights the potential of using drones for blood transportation in urban settings, which can have significant implications for improving the quality of healthcare delivery.

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Section: Literature Reviewmentioning

confidence: 99%

“…However, the handling of uncertainties within the context of drone-based blood transportation remains limited. For instance, Rezaei et al [43] formulated uncertain blood demand as a two-stage PLOS ONE In recent years, the confluence of operations research and logistics expertise has generated an array of drone applications for diverse cargo types. Although the majority of drone delivery literature centers on e-commerce logistics, a substantial body of work has also emerged within emergency and healthcare services, as depicted in Table 1.…”

Section: Literature Reviewmentioning

confidence: 99%

A hierarchical model for strategic and operational planning in blood transportation with drones

Amirsahami,

Barzinpour,

Pishvaee

2023

PLoS ONE

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“…Table 1 summarizes studies on drone-based emergency management from three aspects: the problem features, methods, and application scenarios. Possibly due to the complexities of the studied problems, most studies in Table 1 did not formulate regular models, e.g., IP and MILP [11,12]. As a result, various heuristics and analytical methods were developed.…”

Section: Drones In Emergency Managementmentioning

confidence: 99%

“…As a result, various heuristics and analytical methods were developed. Summarizing the reviewed papers, we can identify and classify the scenarios into three: emergency [11][12][13][14], disaster [15][16][17][18][19][20], and network [14,[21][22][23][24][25]. The disaster scenario mainly concerns post-disaster delivery and various supply and logistics aspects.…”

Section: Drones In Emergency Managementmentioning

confidence: 99%

Drone-Based Emergent Distribution of Packages to an Island from a Land Base

Tian

et al. 2023

Drones

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An island logistics system is vulnerable in emergency conditions and even isolated from land logistics. Drone-based distribution is an emerging solution investigated in this study to transport packages from a land base to the islands. Considering the drone costs, drone landing platforms in islands, and incorporation into the island ground distribution system, this study categorizes the direct, point-to-point, and cyclic bi-stage distribution modes: in the direct mode, the packages are distributed from the drone base station to the customers directly by drones; in the point-to-point mode, the packages are transported to the drone landing platform and then distributed to the customers independently; in the cyclic mode, the packages are distributed from a drone landing platform by a closed route. The modes are formulated, and evaluation metrics and solution methods are developed. In the experiments based on an island case, the models and solution methods are demonstrated, compared, and analyzed. The cyclic bi-stage distribution mode can improve drone flying distance by 50%, and an iterative heuristic algorithm can further improve drone flying distance by 27.8%, and the ground costs by 3.16%, average for the settings of twenty to sixty customers and two to four drone landing platforms. Based on the modeling and experimental studies, managerial implications and possible extensions are discussed.

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A two-stage framework for a resilient medical tourism supply chain considering social aspects and supplier evaluation under uncertainty: a real-case study

Babaei,

Sazvar,

Nayeri

et al. 2024

Ann Oper Res

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Integrating bloodmobiles and drones in a post-disaster blood collection problem considering blood groups

Cited by 8 publications

References 28 publications

A hierarchical model for strategic and operational planning in blood transportation with drones

A hierarchical model for strategic and operational planning in blood transportation with drones

Drone-Based Emergent Distribution of Packages to an Island from a Land Base

A two-stage framework for a resilient medical tourism supply chain considering social aspects and supplier evaluation under uncertainty: a real-case study

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