IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i15p11669-d1205068.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/15/11669/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/15/11669/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Ge, Houtian & Goetz, Stephan J. & Cleary, Rebecca & Yi, Jing & Gómez, Miguel I., 2022. "Facility locations in the fresh produce supply chain: An integration of optimization and empirical methods," International Journal of Production Economics, Elsevier, vol. 249(C).
    3. Maiyar, Lohithaksha M & Thakkar, Jitesh J, 2019. "Environmentally conscious logistics planning for food grain industry considering wastages employing multi objective hybrid particle swarm optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 220-248.
    4. Mona Haji & Laoucine Kerbache & Mahaboob Muhammad & Tareq Al-Ansari, 2020. "Roles of Technology in Improving Perishable Food Supply Chains," Logistics, MDPI, vol. 4(4), pages 1-24, December.
    5. Cholez, Celia & Pauly, Olivier & Mahdad, Maral & Mehrabi, Sepide & Giagnocavo, Cynthia & Bijman, Jos, 2023. "Heterogeneity of inter-organizational collaborations in agrifood chain sustainability-oriented innovations," Agricultural Systems, Elsevier, vol. 212(C).
    6. Nguyen Thi Nha Trang & Thanh-Thuy Nguyen & Hong V. Pham & Thi Thu Anh Cao & Thu Huong Trinh Thi & Javad Shahreki, 2022. "Impacts of Collaborative Partnership on the Performance of Cold Supply Chains of Agriculture and Foods: Literature Review," Sustainability, MDPI, vol. 14(11), pages 1-28, May.
    7. Rahal, Imen & Elloumi, Abdelkarim, 2021. "Inventory management of perishable products : a case of melon in Tunisia," MPRA Paper 118028, University Library of Munich, Germany.
    8. Lejarza, Fernando & Pistikopoulos, Ioannis & Baldea, Michael, 2021. "A scalable real-time solution strategy for supply chain management of fresh produce: A Mexico-to-United States cross border study," International Journal of Production Economics, Elsevier, vol. 240(C).
    9. Liu, Ming & Ding, Yueyu & Chu, Feng & Dolgui, Alexandre & Zheng, Feifeng, 2024. "Robust actions for improving supply chain resilience and viability," Omega, Elsevier, vol. 123(C).
    10. Shafiee, Mohammad & Zare-Mehrjerdi, Yahia & Govindan, Kannan & Dastgoshade, Sohaib, 2022. "A causality analysis of risks to perishable product supply chain networks during the COVID-19 outbreak era: An extended DEMATEL method under Pythagorean fuzzy environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    11. Luo, Na & Olsen, Tava & Liu, Yanping & Zhang, Abraham, 2022. "Reducing food loss and waste in supply chain operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 162(C).
    12. Peyman Akhavan & Maryam Philsoophian, 2023. "Improving of Supply Chain Collaboration and Performance by Using Block Chain Technology as a Mediating Role and Resilience as a Moderating Variable," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(4), pages 4561-4582, December.
    13. Taehyun Ko & Jaeram Lee & Daehyeon Park & Doojin Ryu, 2023. "Supply chain transparency as a signal of ethical production," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(3), pages 1565-1573, April.
    14. Mengfei Chen & Mohamed Kharbeche & Mohamed Haouari & Weihong Grace Guo, 2024. "A simulation-optimization framework for food supply chain network design to ensure food accessibility under uncertainty," Papers 2406.04439, arXiv.org, revised Jun 2024.
    15. Liu, Zhongyi & Li, Mengyu & Lei, Ying & Zhai, Xin, 2022. "A joint strategy based on ordering and insurance for mitigating the effects of supply chain disruption on risk-averse firms," International Journal of Production Economics, Elsevier, vol. 244(C).
    16. Volha Yakavenka & Ioannis Mallidis & Dimitrios Vlachos & Eleftherios Iakovou & Zafeiriou Eleni, 2020. "Development of a multi-objective model for the design of sustainable supply chains: the case of perishable food products," Annals of Operations Research, Springer, vol. 294(1), pages 593-621, November.
    17. Abdolreza Roshani & Philip Walker-Davies & Glenn Parry, 2024. "Designing resilient supply chain networks: a systematic literature review of mitigation strategies," Annals of Operations Research, Springer, vol. 341(2), pages 1267-1332, October.
    18. Manu Sharma & Sudhanshu Joshi & Sunil Luthra & Anil Kumar, 2022. "Managing disruptions and risks amidst COVID-19 outbreaks: role of blockchain technology in developing resilient food supply chains," Operations Management Research, Springer, vol. 15(1), pages 268-281, June.
    19. 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).
    20. Jingwen Li & Ke Jing & Myroslav Khimich & Lixin Shen, 2023. "Optimization of Green Containerized Grain Supply Chain Transportation Problem in Ukraine Considering Disruption Scenarios," Sustainability, MDPI, vol. 15(9), pages 1-21, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11669-:d:1205068. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.