An integer programming approach to the bloodmobile routing problem

Gunpinar, Serkan; Centeno, Grisselle

doi:10.1016/j.tre.2015.12.005

Cited by 55 publications

(23 citation statements)

References 50 publications

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“…Ensafian et al ( 2017 ), Ensafian and Yaghoubi ( 2017 ), Osorio et al ( 2017 ), Hosseinifard and Abbasi ( 2018 ), Clay et al ( 2018 ), Hosseinifard et al ( 2020 ) can be shown as recent examples. In addition, Ghandforoush and Sen ( 2010 ), Şahinyazan et al ( 2015 ), Blake et al ( 2015 ), Gunpinar and Centeno ( 2016 ), Elalouf et al ( 2018 ) focus on the logistics of blood products in the supply chain. The status of the blood supply chain network design and optimization after any disaster and emergency situations is also a sub-area.…”

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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Section: Literature Surveymentioning

confidence: 99%

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

2021

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“…Speaking of transportation, apart from an allocationrouting programming model (IAR) built based on multiple vehicles, multiple supply sites, and multiple objectives, an analytic hierarchy process and MILP were selected to settle relevant problems [23]. In addition, an integer programming model was constructed to identify the number of vehicles needed to implement blood collection operations and to minimise vehicles' travel distance [24]. e aforementioned model also took the uncertainty of blood donation vehicle visits into consideration and determined an optimal route by virtue of the CPLEX solver and the branch-and-price algorithm.…”

Section: Blood Distribution and Schedulingmentioning

confidence: 99%

Dynamic Stochastic Optimization of Emergent Blood Collection and Distribution from Supply Chain Perspective

2021

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In response to emergencies, it is critical to investigate how to deliver emergency supplies efficiently and securely to disaster-affected areas and people. There is no doubt that blood is deemed one of the vital relief supplies, and ensuring smooth blood delivery may substantially alleviate subsequent impacts caused by the disaster. Taking red blood cell products as the research object, this work proposes a four-echelon blood supply chain model. Specifically, it includes blood donors, blood donation houses, blood centres, and hospitals. Furthermore, numerical analysis is provided to test the feasibility of blood collection and distribution schemes and conduct sensitivity analysis to test the impacts of the relevant parameters (e.g., apheresis donation proportion of red blood cells (RBCs), distance between blood donors and blood facilities, and times of blood donation) on the scheme. This research provides some scientific and reasonable support for decision makers and managerial implications for emergency departments and contributes to the study of emergent blood supply chain.

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“…Blood preservation for immediate supply in the case of unexpected demand can be a daunting task. One reason is blood products are perishable commodities so have limited shelf life [3]- [6], which is coupled with the complexity of blood compatibility between different red blood cell types and the stochastic nature of daily blood demand and supply [7]- [9]. Therefore, it is necessary to devise more efficient and effective ways in which blood products can be stored and assigned to individuals in need.…”

Section: Introductionmentioning

confidence: 99%

Computational Intelligence Approach to Dynamic Blood Allocation With ABO-Rhesus Factor Compatibility Under Real-World Scenario

et al. 2020

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The supply chain management of blood products specifically deals with the aspect of efficient planning, implementing, and controlling of the in and out flow processes of blood unity in the blood bank system. Therefore, any improvement in the management of these chains would directly influence the manner in which blood and blood products are distributed to all the various sectors requiring such scarce and precious resources. Generally, the management of blood products is difficult due to the four ABO blood groups, which is further complicated by positive/negative rhesus factors. In this paper, a more simplified and robust dynamic mathematical model is presented for the efficient management of the blood bank. The corresponding sets of governing equations from an existing model are extended to cover the rhesus factors and the solution methods of the newly derived equations are subsequently investigated. In addition, a mathematical representation of the decision making process is presented as a function of the blood bank stockpile. Furthermore, in order to demonstrate the robustness of the developed model and to provide managerial insights, a new global hybrid symbiotic organisms search genetic particle swarm optimization algorithm is developed. Several numerical computations are performed using real-world datasets from the Enugu National Blood Transfusion Centre, in Nigeria, which fall within the monthly initial blood volume bounds of 300 over a period of eight years (2010-2018). Finally, the experimental results show that the mathematical model and metaheuristic optimization method proposed in this paper offer a better solution approach for blood allocation in dynamic environments. More so, the impact of some essential control parameters on the results are analysed to help the blood bank managers or decision makers to select accurately the desired parameters for optimal results yield.

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An integer programming approach to the bloodmobile routing problem

Cited by 55 publications

References 50 publications

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

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

Dynamic Stochastic Optimization of Emergent Blood Collection and Distribution from Supply Chain Perspective

Computational Intelligence Approach to Dynamic Blood Allocation With ABO-Rhesus Factor Compatibility Under Real-World Scenario

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