A bi-objective blood supply chain model under uncertain donation, demand, capacity and cost: a robust possibilistic-necessity approach

Ghahremani-Nahr, J., Kian, R. ORCID: 0000-0001-8786-6349, Sabet, E. ORCID: 0000-0001-8083-6155 and Akbari, V., 2022. A bi-objective blood supply chain model under uncertain donation, demand, capacity and cost: a robust possibilistic-necessity approach. Operational Research - An International Journal. ISSN 1109-2858

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Abstract

This paper addresses a multi-objective blood supply chain network design, considering economic and environmental aspects. The objective of this model is to simultaneously minimize a blood supply chain operational cost and its logistical carbon footprint. In order to embed the uncertainty of transportation costs, blood demand, capacity of facilities and carbon emission, a novel robust possibilistic-necessity optimization used regarding a hybrid optimistic-pessimistic form. For solving our bi-objective model, three multi-objective decision making approaches including LP-metric, Goal-Programming and Torabi- Hassini methods are examined. These approaches are assessed and ranked with respect to several attributes using a statistical test and TOPSIS method. Our proposed model can accommodate a wide range of decision-makers’ viewpoints with the normalized objective weights, both at the operational or strategic level. The trade-offs between the cost and carbon emission for each method has been depicted in our analyses and a Pareto frontier is determined, using a real case study data of 21 cities in the North-West of Iran considering a 12-month implementation time window.

Item Type: Journal article
Publication Title: Operational Research - An International Journal
Creators: Ghahremani-Nahr, J., Kian, R., Sabet, E. and Akbari, V.
Publisher: Springer Verlag
Date: 12 May 2022
ISSN: 1109-2858
Identifiers:
NumberType
10.1007/s12351-022-00710-4DOI
1544667Other
Divisions: Schools > Nottingham Business School
Record created by: Linda Sullivan
Date Added: 16 Jun 2022 10:15
Last Modified: 16 Jun 2022 10:15
URI: http://irep.ntu.ac.uk/id/eprint/46457

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