Enhancing supply chain resilience under disruption: analysis of the farmed data by Monte Carlo simulation

Publication type: Journal Article
Publication date: 2024-09-02
Taylor & Francis
scimago Q2
wos Q2
SJR: 0.755
CiteScore: 6.3
Impact factor: 3.3
ISSN: 23302674, 23302682
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Khodabandeh-Yalabadi A. et al. Enhancing supply chain resilience under disruption: analysis of the farmed data by Monte Carlo simulation // International Journal of Systems Science: Operations and Logistics. 2024. Vol. 11. No. 1.
GOST all authors (up to 50) Copy
Khodabandeh-Yalabadi A., Sheikhalishahi M., TORABI S. A., Naderpour M., Radmankian A. Enhancing supply chain resilience under disruption: analysis of the farmed data by Monte Carlo simulation // International Journal of Systems Science: Operations and Logistics. 2024. Vol. 11. No. 1.
RIS |
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RIS Copy
TY - JOUR
DO - 10.1080/23302674.2024.2398573
UR - https://www.tandfonline.com/doi/full/10.1080/23302674.2024.2398573
TI - Enhancing supply chain resilience under disruption: analysis of the farmed data by Monte Carlo simulation
T2 - International Journal of Systems Science: Operations and Logistics
AU - Khodabandeh-Yalabadi, Ali
AU - Sheikhalishahi, Mohammad
AU - TORABI, SEYED ALI
AU - Naderpour, Mohsen
AU - Radmankian, AmirHossien
PY - 2024
DA - 2024/09/02
PB - Taylor & Francis
IS - 1
VL - 11
SN - 2330-2674
SN - 2330-2682
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2024_Khodabandeh-Yalabadi,
author = {Ali Khodabandeh-Yalabadi and Mohammad Sheikhalishahi and SEYED ALI TORABI and Mohsen Naderpour and AmirHossien Radmankian},
title = {Enhancing supply chain resilience under disruption: analysis of the farmed data by Monte Carlo simulation},
journal = {International Journal of Systems Science: Operations and Logistics},
year = {2024},
volume = {11},
publisher = {Taylor & Francis},
month = {sep},
url = {https://www.tandfonline.com/doi/full/10.1080/23302674.2024.2398573},
number = {1},
doi = {10.1080/23302674.2024.2398573}
}