A bi-objective robust possibilistic programming model for blood supply chain design in the mass casualty event response phase: a M/M/1/K queuing model with real world application

Mahsa Pouraliakbari-Mamaghani, Mohammad Mohammadi, Alireza Arshadi-Khamseh and Bahman Naderi

International Journal of Operational Research, 2021, vol. 42, issue 2, 229-275

Abstract: This paper presents a bi-objective blood supply chain design model for disaster relief. The model aims to simultaneously minimise the total costs of the supply chain, the trade-off between the total expected waiting times of patients in hospitals and the average hospital idle-time probability, unsatisfied demands and the average delivery time from mobile blood facilities to healthcare centres as the first, second, third and fourth objective functions. Since the critical parameters are tainted with great degree of epistemic uncertainty, basic chance constraint programming (BCCP) and robust fuzzy chance constraint programming (RFCCP) are utilised to deal with the uncertain nature of the supply chain. In order to solve the proposed model, two different multiple objective decision making approaches are used. The applicability of the proposed model for earthquake response phase is demonstrated via a real case study in a region of Iran. Useful managerial insights are also provided through conducting some sensitivity analyses.

Keywords: disaster management; blood supply chain network design; queuing theory; ε-constraint method; TH method; waiting times; robust possibilistic programming. (search for similar items in EconPapers)
Date: 2021
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