A robust stochastic bi-objective model for blood inventory-distribution management in a blood supply chain
Seyed Mohammad Hajimolana,
Armin Jabbarzadeh and
Seyed Esmaeil Najafi
European Journal of Industrial Engineering, 2020, vol. 14, issue 3, 369-403
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. (search for similar items in EconPapers)
References: Add references at CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ids:eujine:v:14:y:2020:i:3:p:369-403
Access Statistics for this article
More articles in European Journal of Industrial Engineering from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().