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Reducing food losses and carbon emission by using autonomous control – A simulation study of the intelligent container

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  • Haass, Rasmus
  • Dittmer, Patrick
  • Veigt, Marius
  • Lütjen, Michael

Abstract

During the past decades bananas were imported to Europe in reefer vessels. Often, these vessels returned to Central America empty. This resulted in high carbon emissions and high costs. Therefore, importers switched to reefer containers which are shipped to Europe by liner cargo services. However, the amount of spoiled bananas increased with that change. Now a research project has developed the so called “Intelligent Container”. This Intelligent Container is able to calculate the green life of its cargo and this leads to the feasibility of quality driven distribution. Thus, the losses of bananas should be decreased and both transport costs and carbon emissions be reduced even further.

Suggested Citation

  • Haass, Rasmus & Dittmer, Patrick & Veigt, Marius & Lütjen, Michael, 2015. "Reducing food losses and carbon emission by using autonomous control – A simulation study of the intelligent container," International Journal of Production Economics, Elsevier, vol. 164(C), pages 400-408.
    • Handle: RePEc:eee:proeco:v:164:y:2015:i:c:p:400-408
    DOI: 10.1016/j.ijpe.2014.12.013
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    1. Rong, Aiying & Akkerman, Renzo & Grunow, Martin, 2011. "An optimization approach for managing fresh food quality throughout the supply chain," International Journal of Production Economics, Elsevier, vol. 131(1), pages 421-429, May.
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    4. Sazvar, Z. & Mirzapour Al-e-hashem, S.M.J. & Govindan, K. & Bahli, B., 2016. "A novel mathematical model for a multi-period, multi-product optimal ordering problem considering expiry dates in a FEFO system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 232-261.
    5. Bogataj, David & Bogataj, Marija & Hudoklin, Domen, 2017. "Reprint of “Mitigating risks of perishable products in the cyber-physical systems based on the extended MRP model”," International Journal of Production Economics, Elsevier, vol. 194(C), pages 113-125.
    6. Na Luo & Tava Lennon Olsen & Yanping Liu, 2021. "A Conceptual Framework to Analyze Food Loss and Waste within Food Supply Chains: An Operations Management Perspective," Sustainability, MDPI, vol. 13(2), pages 1-21, January.
    7. Tamvada, Srinivas Subramanya & Mansouri, Bahareh & Hassini, Elkafi & Pribytkov, Theodore, 2021. "An integer programming model and directed Steiner-forest based heuristic for routing less-than-truckload freight," International Journal of Production Economics, Elsevier, vol. 232(C).
    8. Ali Saeed Almuflih & Janpriy Sharma & Mohit Tyagi & Arvind Bhardwaj & Mohamed Rafik Noor Mohamed Qureshi & Nawaf Khan, 2022. "Leveraging the Dynamics of Food Supply Chains towards Avenues of Sustainability," Sustainability, MDPI, vol. 14(12), pages 1-15, June.
    9. Prem Vrat & Rachita Gupta & Aman Bhatnagar & Devendra Kumar Pathak & Vijayta Fulzele, 2018. "Literature review analytics (LRA) on sustainable cold-chain for perishable food products: research trends and future directions," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 601-627, November.
    10. Valentas Gruzauskas & Aurelija Burinskiene & Andrius Krisciunas, 2023. "Application of Information-Sharing for Resilient and Sustainable Food Delivery in Last-Mile Logistics," Mathematics, MDPI, vol. 11(2), pages 1-21, January.
    11. Bogataj, David & Bogataj, Marija & Hudoklin, Domen, 2017. "Mitigating risks of perishable products in the cyber-physical systems based on the extended MRP model," International Journal of Production Economics, Elsevier, vol. 193(C), pages 51-62.
    12. Dulebenets, Maxim A. & Ozguven, Eren Erman, 2017. "Vessel scheduling in liner shipping: Modeling transport of perishable assets," International Journal of Production Economics, Elsevier, vol. 184(C), pages 141-156.
    13. Du, Jiaoman & Zhou, Jiandong & Li, Xiang & Li, Lei & Guo, Ao, 2021. "Integrated self-driving travel scheme planning," International Journal of Production Economics, Elsevier, vol. 232(C).

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