Diverse-seasons-nested-in-periods mathematical models for investigating the economic effects of supply chain planning under simultaneous seasonal fluctuations

Publication typeJournal Article
Publication date2024-03-12
scimago Q2
wos Q2
SJR0.755
CiteScore6.3
Impact factor3.3
ISSN23302674, 23302682
Information Systems
Management Information Systems
Information Systems and Management
Management Science and Operations Research
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Supply Chain Analytics
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International Journal of Management Science and Engineering Management
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Taylor & Francis
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Hussaini Z., Nemati A., Paydar M. H. Diverse-seasons-nested-in-periods mathematical models for investigating the economic effects of supply chain planning under simultaneous seasonal fluctuations // International Journal of Systems Science: Operations and Logistics. 2024. Vol. 11. No. 1.
GOST all authors (up to 50) Copy
Hussaini Z., Nemati A., Paydar M. H. Diverse-seasons-nested-in-periods mathematical models for investigating the economic effects of supply chain planning under simultaneous seasonal fluctuations // International Journal of Systems Science: Operations and Logistics. 2024. Vol. 11. No. 1.
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RIS Copy
TY - JOUR
DO - 10.1080/23302674.2024.2328783
UR - https://doi.org/10.1080/23302674.2024.2328783
TI - Diverse-seasons-nested-in-periods mathematical models for investigating the economic effects of supply chain planning under simultaneous seasonal fluctuations
T2 - International Journal of Systems Science: Operations and Logistics
AU - Hussaini, Zahra
AU - Nemati, Arash
AU - Paydar, Mohammad Hossein
PY - 2024
DA - 2024/03/12
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_Hussaini,
author = {Zahra Hussaini and Arash Nemati and Mohammad Hossein Paydar},
title = {Diverse-seasons-nested-in-periods mathematical models for investigating the economic effects of supply chain planning under simultaneous seasonal fluctuations},
journal = {International Journal of Systems Science: Operations and Logistics},
year = {2024},
volume = {11},
publisher = {Taylor & Francis},
month = {mar},
url = {https://doi.org/10.1080/23302674.2024.2328783},
number = {1},
doi = {10.1080/23302674.2024.2328783}
}