APPLICATION OF MATHEMATICAL MODELING IN SUPPLY CHAIN MANAGEMENT: A REVIEW

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

APPLICATION OF MATHEMATICAL MODELING IN SUPPLY CHAIN MANAGEMENT: A REVIEW

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

APPLICATION OF MATHEMATICAL MODELING IN SUPPLY CHAIN MANAGEMENT: A REVIEW

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY

ISSN

0218-348X

e-ISSN

1793-6543

Svazek periodika

33

Číslo periodika v rámci svazku

07

Stát vydavatele periodika

SG - Singapurská republika

Počet stran výsledku

14

Strana od-do

nestránkováno

Kód UT WoS článku

001523992800001

EID výsledku v databázi Scopus

2-s2.0-105010165143