Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/310283 
Year of Publication: 
2022
Citation: 
[Journal:] Logistics [ISSN:] 2305-6290 [Volume:] 6 [Issue:] 4 [Article No.:] 74 [Year:] 2022 [Pages:] 1-16
Publisher: 
MDPI, Basel
Abstract: 
Background: The global dairy market is experiencing a massive transition as dairy farming has recently undergone modernization. As a result, the dairy industry needs to improve its operational efficiencies by implementing effective optimization techniques. Conventional and emerging optimization techniques have already gained momentum in the dairy industry. This study's objective was to explore the optimization techniques developed for or implemented in the dairy supply chain (DSC) and to investigate how these techniques can improve the DSC. Methods: A systematic review approach based on PRISMA guidelines were adopted to conduct this review. The authors used descriptive statistics for statistical analysis. Results: Modernization has led the dairy industry to improve its operational efficiencies by implementing the most effective optimization techniques. Researchers have used mathematical modeling-based methods and are shifting to artificial intelligence (AI) and machine learning (ML) -based approaches in the DSC. The mathematical modeling-based techniques remain dominant (56% of articles), but AI and ML-based techniques are gaining traction (used in around 44% of articles). Conclusions: The review findings show insight into the benefits and implications of optimization techniques in the DSC. This research shows how optimization techniques are associated with every phase of the DSC and how new technologies have affected the supply chain.
Subjects: 
artificial intelligence
dairy industry
machine learning
mathematical modelling
optimization
supply chain
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
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