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Application of Optimization Techniques in the Dairy Supply Chain: A Systematic Review

Author

Listed:
  • Mohit Malik

    (Department of Basic and Applied Sciences, National Institute of Food Technology Entrepreneurship and Management, Kundli, Sonepat 131028, India)

  • Vijay Kumar Gahlawat

    (Department of Basic and Applied Sciences, National Institute of Food Technology Entrepreneurship and Management, Kundli, Sonepat 131028, India)

  • Rahul S Mor

    (Department of Food Engineering, National Institute of Food Technology Entrepreneurship and Management, Kundli, Sonepat 131028, India)

  • Vijay Dahiya

    (Department of Business Administration, Maharaja Surajmal Institute, C-4, Janakpuri, New Delhi 110058, India)

  • Mukheshwar Yadav

    (Department of Mechanical Engineering, CUIET, Chitkara University, Rajpura 140401, India)

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.

Suggested Citation

  • Mohit Malik & Vijay Kumar Gahlawat & Rahul S Mor & Vijay Dahiya & Mukheshwar Yadav, 2022. "Application of Optimization Techniques in the Dairy Supply Chain: A Systematic Review," Logistics, MDPI, vol. 6(4), pages 1-16, October.
    • Handle: RePEc:gam:jlogis:v:6:y:2022:i:4:p:74-:d:944385
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    References listed on IDEAS

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    1. Bilge Bilgen & Yelda Çelebi, 2013. "Integrated production scheduling and distribution planning in dairy supply chain by hybrid modelling," Annals of Operations Research, Springer, vol. 211(1), pages 55-82, December.
    2. Mor, Rahul S & Bhardwaj, Arvind & Singh, Sarbjit, 2018. "A structured-literature-review of the supply chain practices in dairy industry," Journal of Operations and Supply Chain Management (JOSCM), Fundação Getulio Vargas, Escola de Administração de Empresas de São Paulo (FGV EAESP), vol. 11(01), June.
    3. Saurabh Sharma & Vijay Kumar Gahlawat & Kumar Rahul & Rahul S Mor & Mohit Malik, 2021. "Sustainable Innovations in the Food Industry through Artificial Intelligence and Big Data Analytics," Logistics, MDPI, vol. 5(4), pages 1-16, September.
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    7. Jabir E. & Vinay V. Panicker & R. Sridharan, 2022. "Environmental friendly route design for a milk collection problem: the case of an Indian dairy," International Journal of Production Research, Taylor & Francis Journals, vol. 60(3), pages 912-941, February.
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    Cited by:

    1. Noha A. Mostafa & Omar Eldebaiky, 2023. "A Sustainable Two-Echelon Logistics Model with Shipment Consolidation," Logistics, MDPI, vol. 7(1), pages 1-14, March.
    2. Mohit Malik & Vijay Kumar Gahlawat & Rahul S Mor & Amin Hosseinian-Far, 2024. "Towards white revolution 2.0: challenges and opportunities for the industry 4.0 technologies in Indian dairy industry," Operations Management Research, Springer, vol. 17(3), pages 811-832, September.

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