A DEA-based simulation-optimisation approach to design a resilience plasma supply chain network: a case study of the COVID-19 outbreak
Küçük Resim Yok
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis Ltd
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This study develops a novel multi-objective mathematical model for a Plasma Supply Chain Network (PSCN) in order to maximise the coverage of blood donors during periods and minimise the blood transportation costs between different nodes, relocation cost of temporary mobile facilities, inventory holding cost of the blood, and the costs of newly established blood centres. Therefore, the major contribution of this work is the simultaneous consideration of resiliency and efficiency in the proposed PCN during the COVID-19 outbreak. To address the uncertain parameters, Stochastic Chance-Constrained Programming (SCCP) method is applied to the model. Additionally, to solve the PSCN model, the & epsilon;-constraint method is employed for small- and medium-sized problems and then a multi-objective invasive weed optimisation (MOIWO) algorithm is implemented for large-sized problems. To validate the suggested methodology, a variety of problem instances is designed and solved using the solution techniques, considering two assessment metrics of Hyper Volume (HV) and Min Ideal Distance (MID). Moreover, a real case study and sensitivity analyses on significant parameters are conducted to configure the optimal network. Eventually, the obtained results are examined and useful decision aids are suggested.
Açıklama
Anahtar Kelimeler
Plasma Supply Chain Network, Resilience, Efficiency, Covid-19 Pandemic, Stochastic Chance-Constrained Programming, Simulation-Optimisation Model, >
Kaynak
International Journal of Systems Science-Operations & Logistics
WoS Q Değeri
N/A
Scopus Q Değeri
Q1
Cilt
10
Sayı
1
