Exploring the Power of Artificial Intelligence in Supply Chain Management: A Literature Review on the Artificial Intelligence Applications and Tools Used in Supply Chains and Their Distribution According to the SCOR Method

被引:0
作者
Harrir, Mohamed Mounir [1 ]
Triqui Sari, Lamia [1 ]
机构
[1] Univ Tlemcen, Chetouane, Tlemcen, Algeria
关键词
Artificial Intelligence (AI); Supply Chain Management (SCM); Supply Chain Operations Reference (SCOR) Model; Predictive Analytics; Supply Chain 4.0; FUZZY-LOGIC APPROACH; EXPERT-SYSTEM; MULTIAGENT SYSTEM; NEURAL-NETWORK; OPTIMIZATION ALGORITHM; TRADE-OFF; MODEL; SELECTION; PERFORMANCE; INTEGRATION;
D O I
10.1080/10429247.2024.2406125
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Since the beginning of the 21st century, supply chains have witnessed rapid and significant changes along with considerable developments due to the convergence between technology and globalization. The present study aims primarily to provide insight into the artificial intelligence (AI) tools used in Supply Chain Management Processes using the Supply Chain Operations Reference (SCOR) approach. It also seeks to examine the way AI tools can be applied to the outputs of each process and each application. The study follows a four-step systematic review approach that mainly involves literature collection between the years 2000 and 2022, descriptive analysis, category selection, and material evaluation. The main purpose of this work is to improve the capacity of making the most appropriate decisions through the use of the most suitable AI tools for each function and each process within supply chains in order to ensure the best management of these chains.
引用
收藏
页数:22
相关论文
共 170 条
  • [91] An integrated Delphi - fuzzy logic approach for measuring supply chain resilience: an illustrative case from manufacturing industry
    Kumar, Siva
    Anbanandam, Ramesh
    [J]. MEASURING BUSINESS EXCELLENCE, 2019, 23 (03) : 350 - 375
  • [92] Integration of artificial neural network and MADA methods for green supplier selection
    Kuo, R. J.
    Wang, Y. C.
    Tien, F. C.
    [J]. JOURNAL OF CLEANER PRODUCTION, 2010, 18 (12) : 1161 - 1170
  • [93] A hybrid ant colony optimization-variable neighborhood descent approach for the cumulative capacitated vehicle routing problem
    Kyriakakis, Nikolaos A.
    Marinaki, Magdalene
    Marinakis, Yannis
    [J]. COMPUTERS & OPERATIONS RESEARCH, 2021, 134
  • [94] A POPMUSIC approach for the Multi-Depot Cumulative Capacitated Vehicle Routing Problem
    Lalla-Ruiz, Eduardo
    Voss, Stefan
    [J]. OPTIMIZATION LETTERS, 2020, 14 (03) : 671 - 691
  • [95] Lau H. C. W., 2002, Logistics Information Management, V15, P271, DOI 10.1108/09576050210436110
  • [96] Application of the Neural Decision Tree approach for prediction of petroleum production
    Li, X.
    Chan, C. W.
    Nguyen, H. H.
    [J]. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2013, 104 : 11 - 16
  • [97] Agri-food supply chain network disruption propagation and recovery based on cascading failure
    Li, Zhuyue
    Zhao, Peixin
    Han, Xue
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2022, 589
  • [98] Predicting supply chain performance based on SCOR® metrics and multilayer perceptron neural networks
    Lima-Junior, Francisco Rodrigues
    Ribeiro Carpinetti, Luiz Cesar
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2019, 212 : 19 - 38
  • [99] An innovative machine learning model for supply chain management
    Lin, Haifeng
    Lin, Ji
    Wang, Fang
    [J]. JOURNAL OF INNOVATION & KNOWLEDGE, 2022, 7 (04):
  • [100] A branch & cut/metaheuristic optimization of financial supply chain based on input-output network flows: investigating the Iranian orthopedic footwear
    Liu, Peide
    Hendalianpour, Ayad
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2021, 41 (02) : 2561 - 2579