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Design of an Optimal Robust Possibilistic Model in the Distribution Chain Network of Agricultural Products with High Perishability under Uncertainty

Author

Listed:
  • Amir Daneshvar

    (Department of Information Technology Management, Electronic Branch, Islamic Azad University, Tehran 1477893855, Iran)

  • Reza Radfar

    (Department of Technology Management, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran)

  • Peiman Ghasemi

    (Department of Business Decisions and Analytics, University of Vienna, Kolingasse 14-16, 1090 Vienna, Austria)

  • Mahmonir Bayanati

    (Department of Management, Faculty of Technology and Industrial Management, West Tehran Branch, Islamic Azad University, Tehran 1477893855, Iran)

  • Adel Pourghader Chobar

    (Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin 3471993116, Iran)

Abstract

In this article, the modeling of a distribution network problem of agricultural products with high perishability under uncertainty is discussed. The designed model has three levels of suppliers, distribution centers, and retailers, in which suppliers can directly or indirectly meet retailers’ demand. Due to agricultural product distribution network unpredictability, robust possibilistic optimization (RPO) has been applied. This model is innovative and takes uncertainty into account. The findings show that uncertainty increases network demand. Supply, distribution, maintenance, and order expenses have grown. By examining the rate of perishability of agricultural products, it has been revealed that, with the growth of this rate, the costs have increased according to the ordering and spoilage of the products. The genetic algorithm (GA), whale optimization algorithm (WOA), and arithmetic optimization algorithm (AOA) have also been applied to analyze the model. The calculations on 10 sample problems in larger sizes show that the AOA has the best performance in achieving near-optimal solutions. Conversely, the WOA has the lowest computing time compared to other meta-heuristic algorithms. Additionally, the statistical test results show no significant difference between the average calculation time and the objective function among the applied algorithms.

Suggested Citation

  • Amir Daneshvar & Reza Radfar & Peiman Ghasemi & Mahmonir Bayanati & Adel Pourghader Chobar, 2023. "Design of an Optimal Robust Possibilistic Model in the Distribution Chain Network of Agricultural Products with High Perishability under Uncertainty," Sustainability, MDPI, vol. 15(15), pages 1-22, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11669-:d:1205068
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    References listed on IDEAS

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    1. Mogale, D.G. & Kumar, Mukesh & Kumar, Sri Krishna & Tiwari, Manoj Kumar, 2018. "Grain silo location-allocation problem with dwell time for optimization of food grain supply chain network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 40-69.
    2. Juan Carlos Pérez-Mesa & Laura Piedra-Muñoz & Emilio Galdeano-Gómez & Cynthia Giagnocavo, 2021. "Management Strategies and Collaborative Relationships for Sustainability in the Agrifood Supply Chain," Sustainability, MDPI, vol. 13(2), pages 1-16, January.
    3. Gholami-Zanjani, Seyed Mohammad & Klibi, Walid & Jabalameli, Mohammad Saeed & Pishvaee, Mir Saman, 2021. "The design of resilient food supply chain networks prone to epidemic disruptions," International Journal of Production Economics, Elsevier, vol. 233(C).
    4. Showkat Ahmad Bhat & Nen-Fu Huang & Ishfaq Bashir Sofi & Muhammad Sultan, 2021. "Agriculture-Food Supply Chain Management Based on Blockchain and IoT: A Narrative on Enterprise Blockchain Interoperability," Agriculture, MDPI, vol. 12(1), pages 1-25, December.
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    Cited by:

    1. Misagh Rahbari & Reza Tavakkoli-Moghaddam & Seyed Hossein Razavi Hajiagha & Mohammad Javad Jafari, 2026. "Wheat Supply Chain Network Design: Lesson for Resilience and Sustainability in a Situation of War and Crisis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 17(2), pages 5972-6016, April.

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