Title: A robust stochastic bi-objective model for blood inventory-distribution management in a blood supply chain
Authors: Hadis Derikvand; Seyed Mohammad Hajimolana; Armin Jabbarzadeh; Seyed Esmaeil Najafi
Addresses: Department of Industrial Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran ' Department of Industrial Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran ' Department of Systems Engineering, École de Technologie Supérieure (ETS), Montreal, Canada ' Department of Industrial Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran
Abstract: Providing blood units in a blood supply chain should be effective, appropriate and well-organised since it directly affects the health of individuals, and if not provided promptly, can even lead to the death of patients. This study presents a robust stochastic bi-objective programming model for an inventory-distribution problem in a blood supply chain, the first objective of which attempts to minimise the total number of shortages and wastages and the second objective maximises the connection between two different types of hospitals. The blood supply chain under investigation includes one blood centre, type-1 and type-2 hospitals and patients. Mathematical approximations are employed to remove the nonlinear terms, and a hybrid solution approach, combining the ε-constraint and the Lagrangian relaxation method, is applied to solve the proposed bi-objective model. Finally, the model is implemented and analysed using the data inspired by a real case study in Iran to show its potential applicability [Received: 24 September 2018; Revised: 15 June 2019; Revised: 1 September 2019; Accepted: 1 September 2019]
Keywords: blood supply chain; robust programming approach; ε-constraint; Lagrangian relaxation approach; blood inventory-distribution management.
European Journal of Industrial Engineering, 2020 Vol.14 No.3, pp.369 - 403
Published online: 08 Jun 2020 *Full-text access for editors Access for subscribers Purchase this article Comment on this article