Bi-objective emergency blood supply chain network design in earthquake considering earthquake magnitude: a comprehensive study with real world application

Soheyl Khalilpourazari () and Alireza Arshadi Khamseh ()
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Soheyl Khalilpourazari: Kharazmi University
Alireza Arshadi Khamseh: Kharazmi University

Annals of Operations Research, 2019, vol. 283, issue 1, No 16, 355-393

Abstract: Abstract This research proposes a new multi-objective mathematical model to design efficient and effective blood supply chain network in earthquakes. For the first time in this field of knowledge, the devastating impact of earthquake destruction radius is considered on blood supply chain network based on its magnitude. Two different transportation means, with variant speed and capacity, are employed to carry the blood from blood collection centers to blood centers. However, the number of available conveyors is limited in each site. To solve the proposed multi-objective mixed integer linear programming model, five multi-objective decision making methods as well as the lexicographic weighted Tchebycheff method are utilized to provide the decision maker with Pareto optimal solutions. Further, the application of the proposed multi-objective mathematical model is investigated in a real-world case study using data from the latest earthquakes in one of the recent activated faults of Iran’s capital, Tehran, which is considered to be a potential place for a severe earthquake. Using different solution approaches, various Pareto optimal solutions are obtained for the case study. The results indicated that the proposed mathematical model is able to design the most cost and time efficient blood supply chain in a severe earthquake. At the end, sensitivity analyses are performed to explore the effects of any changes in main parameters of the multi-objective mathematical model on the objective functions value to demonstrate the most critical parameter.

Keywords: Blood supply chain; Supply chain network design; Multi-objective decision making; Location and allocation; Multi-objective optimization; Lexicographic weighted Tchebycheff (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (18)

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DOI: 10.1007/s10479-017-2588-y

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