APPLICATION OF MATHEMATICAL MODELING IN SUPPLY CHAIN MANAGEMENT: A REVIEW
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F25%3A43910084" target="_blank" >RIV/60076658:12310/25:43910084 - isvavai.cz</a>
Result on the web
<a href="https://www.worldscientific.com/doi/epdf/10.1142/S0218348X25300077" target="_blank" >https://www.worldscientific.com/doi/epdf/10.1142/S0218348X25300077</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1142/S0218348X25300077" target="_blank" >10.1142/S0218348X25300077</a>
Alternative languages
Result language
angličtina
Original language name
APPLICATION OF MATHEMATICAL MODELING IN SUPPLY CHAIN MANAGEMENT: A REVIEW
Original language description
Mathematical modeling plays a critical role in modern supply chain management (SCM) by enabling optimization, forecasting, and informed decision-making across complex networks. This review synthesizes recent advancements in mathematical modeling across five key domains of SCM: demand forecasting, inventory control, logistics and distribution, sustainability, and the integration of emerging technologies. We explore a wide array of modeling techniques, including time-series analysis, stochastic models, optimization algorithms, and machine learning, highlighting their applications, strengths, and limitations. Special attention is given to the evolving roles of artificial intelligence (AI), Internet of Things (IoT), and digital twins in enhancing model responsiveness and adaptability. Despite these advancements, challenges remain in achieving model transparency, scalability, and seamless integration with real-time technologies such as IoT and digital twins. Future research should focus on developing more interpretable machine learning models, improving data governance, and fostering cross-domain collaboration to enhance decision-making across the supply chain. This review provides a foundational understanding while identifying key gaps and future pathways for innovation in mathematical modeling for supply chain management.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY
ISSN
0218-348X
e-ISSN
1793-6543
Volume of the periodical
33
Issue of the periodical within the volume
07
Country of publishing house
SG - SINGAPORE
Number of pages
14
Pages from-to
nestránkováno
UT code for WoS article
001523992800001
EID of the result in the Scopus database
2-s2.0-105010165143