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Modelling of sustainable food grain supply chain distribution system: a bi-objective approach

Author

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  • D. G. Mogale
  • Naoufel Cheikhrouhou
  • Manoj Kumar Tiwari

Abstract

Growing food demand, environmental degradation, post-harvest losses and the dearth of resources encourage the decision makers from developing nations to integrate the economic and environmental aspects in food supply chain network design. This paper aims to develop a bi-objective decision support model for sustainable food grain supply chain considering an entire network of procurement centres, central, state and district level warehouses, and fair price shops. The model seeks to minimise the cost and carbon dioxide emission simultaneously. The model covers several problem peculiarities such as multi-echelon, multi-period, multi-modal transportation, multiple sourcing and distribution, emission caused due to various motives, heterogeneous capacitated vehicles and limited availability, and capacitated warehouses. Multiple realistic problem instances are solved using the two Pareto based multi-objective algorithms. Sensitivity analysis results imply that the decision makers should establish a sufficient number of warehouses in each producing and consuming states by maintaining the suitable balance between the two objectives. Various policymakers like Food Corporation of India, logistics providers and state government agencies will be benefited from this research study.

Suggested Citation

  • D. G. Mogale & Naoufel Cheikhrouhou & Manoj Kumar Tiwari, 2020. "Modelling of sustainable food grain supply chain distribution system: a bi-objective approach," International Journal of Production Research, Taylor & Francis Journals, vol. 58(18), pages 5521-5544, September.
    • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:18:p:5521-5544
    DOI: 10.1080/00207543.2019.1669840
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    Cited by:

    1. Tapan Kumar Datta & Sayantan Datta & Adrijit Goswami, 2024. "A sustainable bi-objective inventory model with source-based emissions and plan-based green investments under inflation and the present value of money," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 34(1), pages 91-117.
    2. Jiaxing Wang & Sibin Gao & Zhejun Tang & Dapeng Tan & Bin Cao & Jing Fan, 2023. "A context-aware recommendation system for improving manufacturing process modeling," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1347-1368, March.
    3. Soheyl Khalilpourazari & Saman Khalilpourazary & Aybike Özyüksel Çiftçioğlu & Gerhard-Wilhelm Weber, 2021. "Designing energy-efficient high-precision multi-pass turning processes via robust optimization and artificial intelligence," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1621-1647, August.
    4. Maheshwari, Pratik & Kamble, Sachin & Belhadi, Amine & Venkatesh, Mani & Abedin, Mohammad Zoynul, 2023. "Digital twin-driven real-time planning, monitoring, and controlling in food supply chains," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    5. Naila Fares & Jaime Lloret & Vikas Kumar & Sander de Leeuw & Liz Barnes, 2024. "Optimisation of multi‐tier supply chain distribution networks with corporate social responsibility concerns in fast‐fashion retail," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 31(1), pages 311-330, January.
    6. Sumanta Das & Abhiram Yadav Myla & Akhilesh Barve & Anil Kumar & Naresh Chandra Sahu & Kamalakanta Muduli & Sunil Luthra, 2023. "A systematic assessment of multi‐dimensional risk factors for sustainable development in food grain supply chains: A business strategic prospective analysis," Business Strategy and the Environment, Wiley Blackwell, vol. 32(8), pages 5536-5562, December.
    7. Xifeng Tang & Jiantao Wu & Rui Li, 2020. "Efficient Allocation of Customers to Facilities in the Multi-Objective Sustainable Location Problem," Sustainability, MDPI, vol. 12(18), pages 1-12, September.
    8. Vinay Surendra Yadav & A. R. Singh & Rakesh D. Raut & Naoufel Cheikhrouhou, 2023. "Blockchain drivers to achieve sustainable food security in the Indian context," Annals of Operations Research, Springer, vol. 327(1), pages 211-249, August.
    9. Reza Eslamipoor & Abbas Sepehriyar, 2024. "Promoting green supply chain under carbon tax, carbon cap and carbon trading policies," Business Strategy and the Environment, Wiley Blackwell, vol. 33(5), pages 4901-4912, July.
    10. Kumar, Shashank & Raut, Rakesh D. & Queiroz, Maciel M. & Narkhede, Balkrishna E., 2021. "Mapping the barriers of AI implementations in the public distribution system: The Indian experience," Technology in Society, Elsevier, vol. 67(C).
    11. Jahani, Hamed & Abbasi, Babak & Sheu, Jiuh-Biing & Klibi, Walid, 2024. "Supply chain network design with financial considerations: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 312(3), pages 799-839.
    12. Xing Chen & Eunmi Jang, 2022. "A Sustainable Supply Chain Network Model Considering Carbon Neutrality and Personalization," Sustainability, MDPI, vol. 14(8), pages 1-23, April.
    13. Dhirendra Prajapati & Fuli Zhou & Ashish Dwivedi & Tripti Singh & Lakshay Lakshay & Saurabh Pratap, 2022. "Sustainable Agro-Food Supply Chain in E-Commerce: Towards the Circular Economy," Sustainability, MDPI, vol. 14(14), pages 1-19, July.
    14. Gustavo Rodrigues de Morais & Yuri Clements Daglia Calil & Gabriel Faria de Oliveira & Rodney Rezende Saldanha & Carlos Andrey Maia, 2023. "A Sustainable Location Model of Transshipment Terminals Applied to the Expansion Strategies of the Soybean Intermodal Transport Network in the State of Mato Grosso, Brazil," Sustainability, MDPI, vol. 15(2), pages 1-27, January.
    15. Chethana Chandrasiri & Senevi Kiridena & Subodha Dharmapriya & Asela K. Kulatunga, 2024. "Adoption of Multi-Modal Transportation for Configuring Sustainable Agri-Food Supply Chains in Constrained Environments," Sustainability, MDPI, vol. 16(17), pages 1-13, September.

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