IDEAS home Printed from https://ideas.repec.org/a/spr/opsear/v59y2022i4d10.1007_s12597-022-00594-0.html
   My bibliography  Save this article

Multi-objective model for perishable food logistics networks design considering availability and access

Author

Listed:
  • Javier Arturo Orjuela-Castro

    (Universidad Distrital Francisco José de Caldas)

  • Juan Pablo Orejuela-Cabrera

    (Universidad del Valle)

  • Wilson Adarme-Jaimes

    (Universidad Nacional de Colombia)

Abstract

The supply chains of perishable food (PFSC) fresh, present imbalances between supply and demand, in times of supply deficit is necessary to guarantee the food security through the availability, the access and other pillars. In the PFSC losses are highest, whereby the delivery times must be low to guarantee the availability. For the access, must be include the largest number of retailed storekeepers, thus monopolies from large hypermarkets are avoided. In this context, the modeling In PFSC presents big challenges such as the inclusion of delivery times, losses and fresh food biophysical specific conditions which depend of the transport time and storage, the configuration and the number of echelons on the PFSC. In this article, a multiobjective, multiproduct and multi-echelon for perishable food logistics networks design mixed linear programming model is presented. The model allows determining the best configuration so that the different actors of the PFSC, so that could move closer to more efficient borders. The model considers the losses in perishable food derived from the impacts caused by changes in temperature (T°) and relative humidity (RH), on a mountainous environment of developing countries. It is solved in AMPL through e-constrains method. The model is applied in a case study around the perishable fruit supply chains (PFrSC). The information to the model parameterization was obtained through surveys done to the actors of the different echelons of PFrSC during a 4-year period that were complemented with secondary information from public and private enterprises.

Suggested Citation

  • Javier Arturo Orjuela-Castro & Juan Pablo Orejuela-Cabrera & Wilson Adarme-Jaimes, 2022. "Multi-objective model for perishable food logistics networks design considering availability and access," OPSEARCH, Springer;Operational Research Society of India, vol. 59(4), pages 1244-1270, December.
    • Handle: RePEc:spr:opsear:v:59:y:2022:i:4:d:10.1007_s12597-022-00594-0
    DOI: 10.1007/s12597-022-00594-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12597-022-00594-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12597-022-00594-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ohad Eisenhandler & Michal Tzur, 2019. "The Humanitarian Pickup and Distribution Problem," Operations Research, INFORMS, vol. 67(1), pages 10-32, January.
    2. Soto-Silva, Wladimir E. & Nadal-Roig, Esteve & González-Araya, Marcela C. & Pla-Aragones, Lluis M., 2016. "Operational research models applied to the fresh fruit supply chain," European Journal of Operational Research, Elsevier, vol. 251(2), pages 345-355.
    3. de Keizer, Marlies & Akkerman, Renzo & Grunow, Martin & Bloemhof, Jacqueline M. & Haijema, Rene & van der Vorst, Jack G.A.J., 2017. "Logistics network design for perishable products with heterogeneous quality decay," European Journal of Operational Research, Elsevier, vol. 262(2), pages 535-549.
    4. Ohad Eisenhandler & Michal Tzur, 2019. "A Segment-Based Formulation and a Matheuristic for the Humanitarian Pickup and Distribution Problem," Transportation Science, INFORMS, vol. 53(5), pages 1389-1408, September.
    5. Ahumada, Omar & Villalobos, J. Rene, 2009. "Application of planning models in the agri-food supply chain: A review," European Journal of Operational Research, Elsevier, vol. 196(1), pages 1-20, July.
    6. Farahani, Reza Zanjirani & Rezapour, Shabnam & Drezner, Tammy & Fallah, Samira, 2014. "Competitive supply chain network design: An overview of classifications, models, solution techniques and applications," Omega, Elsevier, vol. 45(C), pages 92-118.
    7. Goetschalckx, Marc & Vidal, Carlos J. & Dogan, Koray, 2002. "Modeling and design of global logistics systems: A review of integrated strategic and tactical models and design algorithms," European Journal of Operational Research, Elsevier, vol. 143(1), pages 1-18, November.
    8. Peng, Peng & Snyder, Lawrence V. & Lim, Andrew & Liu, Zuli, 2011. "Reliable logistics networks design with facility disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1190-1211, September.
    9. Yu, Min & Nagurney, Anna, 2013. "Competitive food supply chain networks with application to fresh produce," European Journal of Operational Research, Elsevier, vol. 224(2), pages 273-282.
    10. Gunasekaran, Angappa & Ngai, Eric W.T., 2012. "The future of operations management: An outlook and analysis," International Journal of Production Economics, Elsevier, vol. 135(2), pages 687-701.
    11. Siya Ram Meena & Shambhu D. Meena & Saurabh Pratap & Rakesh Patidar & Yash Daultani, 2019. "Strategic analysis of the Indian agri-food supply chain," OPSEARCH, Springer;Operational Research Society of India, vol. 56(3), pages 965-982, September.
    12. 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.
    13. T. V. S. R. K. Prasad & Kolla Srinivas & C. Srinivas, 2020. "Investigations into control strategies of supply chain planning models: a case study," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 874-907, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Somsai, Thanatporn & Pongcharoen, Pupong & Hicks, Christian, 2024. "Optimizing sustainable multimodal distribution networks in the context of carbon pricing, with a case study in the Thai sugar industry," Energy, Elsevier, vol. 298(C).

    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. Chintapalli, Prashant & Tang, Christopher S., 2022. "The implications of crop minimum support price in the presence of myopic and strategic farmers," European Journal of Operational Research, Elsevier, vol. 300(1), pages 336-349.
    2. Magdalena Leithner & Christian Fikar, 2022. "A simulation model to investigate impacts of facilitating quality data within organic fresh food supply chains," Annals of Operations Research, Springer, vol. 314(2), pages 529-550, July.
    3. Tuğçe Taşkıner & Bilge Bilgen, 2021. "Optimization Models for Harvest and Production Planning in Agri-Food Supply Chain: A Systematic Review," Logistics, MDPI, vol. 5(3), pages 1-27, August.
    4. Maiyar, Lohithaksha M. & Thakkar, Jitesh J., 2019. "Modelling and analysis of intermodal food grain transportation under hub disruption towards sustainability," International Journal of Production Economics, Elsevier, vol. 217(C), pages 281-297.
    5. Hasani, Aliakbar & Khosrojerdi, Amirhossein, 2016. "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 20-52.
    6. 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).
    7. Lejarza, Fernando & Baldea, Michael, 2022. "An efficient optimization framework for tracking multiple quality attributes in supply chains of perishable products," European Journal of Operational Research, Elsevier, vol. 297(3), pages 890-903.
    8. H. Neil Geismar & Yiwei Huang & Suresh D. Pillai & Chelliah Sriskandarajah & Seokjun Youn, 2020. "Location‐Routing with Conflicting Objectives: Coordinating eBeam Phytosanitary Treatment and Distribution of Mexican Import Commodities," Production and Operations Management, Production and Operations Management Society, vol. 29(6), pages 1506-1531, June.
    9. Esteban Ogazón & Neale R. Smith & Angel Ruiz, 2022. "Reconfiguration of Foodbank Network Logistics to Cope with a Sudden Disaster," Mathematics, MDPI, vol. 10(9), pages 1-20, April.
    10. 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).
    11. Yang, Yongjian & Yin, Yunqiang & Wang, Dujuan & Ignatius, Joshua & Cheng, T.C.E. & Dhamotharan, Lalitha, 2023. "Distributionally robust multi-period location-allocation with multiple resources and capacity levels in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1042-1062.
    12. Víctor M. Albornoz & Gabriel E. Zamora, 2021. "Decomposition-based heuristic for the zoning and crop planning problem with adjacency constraints," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 248-265, April.
    13. Mahmoudi, Monirehalsadat & Shirzad, Khadijeh & Verter, Vedat, 2022. "Decision support models for managing food aid supply chains: A systematic literature review," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    14. Soto-Silva, Wladimir E. & Nadal-Roig, Esteve & González-Araya, Marcela C. & Pla-Aragones, Lluis M., 2016. "Operational research models applied to the fresh fruit supply chain," European Journal of Operational Research, Elsevier, vol. 251(2), pages 345-355.
    15. 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.
    16. Van Engeland, Jens & Beliën, Jeroen & De Boeck, Liesje & De Jaeger, Simon, 2020. "Literature review: Strategic network optimization models in waste reverse supply chains," Omega, Elsevier, vol. 91(C).
    17. Fattahi, Mohammad & Govindan, Kannan & Keyvanshokooh, Esmaeil, 2017. "Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 176-200.
    18. Wishon, C. & Villalobos, J.R. & Mason, N. & Flores, H. & Lujan, G., 2015. "Use of MIP for planning temporary immigrant farm labor force," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 25-33.
    19. Kanokporn Kungwalsong & Abraham Mendoza & Vasanth Kamath & Subramanian Pazhani & Jose Antonio Marmolejo-Saucedo, 2022. "An application of interactive fuzzy optimization model for redesigning supply chain for resilience," Annals of Operations Research, Springer, vol. 315(2), pages 1803-1839, August.
    20. Niu, Yi-Feng & Gao, Zi-You & Lam, William H.K., 2017. "Evaluating the reliability of a stochastic distribution network in terms of minimal cuts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 100(C), pages 75-97.

    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:spr:opsear:v:59:y:2022:i:4:d:10.1007_s12597-022-00594-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.