IDEAS home Printed from https://ideas.repec.org/a/ags/ijamad/335133.html
   My bibliography  Save this article

Efficient Harvesting of Saffron Using Integer Programming

Author

Listed:
  • Kheybari, Siamak
  • Bokaeyan, Amir
  • Yazd, Seyed Ali Naji Nasrabadi

Abstract

Among various products available in agriculture, saffron plays a major role in contributing to Iran's gross domestic product and per capita income growth. Due to shortage of workforce and short duration of harvesting, areas under cultivation of saffron in Iran will be declining in coming years. Thus, proper planning for optimum use of workforce is one of the most important techniques to access efficient harvesting. In this regard, an integer programming model is proposed to solve the problem in this paper. Number of working shift and working hours in each shift are among decision variables in the proposed model, which satisfy the objective function, i.e. minimizing the total cost of workforce, with constrains including number of working hours in each shift, speed of workforce, number of fields that should be harvested in each day and relationship between working hours of each worker and the cost allocated­­­­. To evaluate the proposed model, we employ the data collected from fields located in different areas of Qaen, South Khorasan province, Iran. By comparing the output of the proposed model to the real situation, the ability of the model is confirmed. Finally, concluding remarks and suggestions for future research are provided.

Suggested Citation

  • Kheybari, Siamak & Bokaeyan, Amir & Yazd, Seyed Ali Naji Nasrabadi, 2020. "Efficient Harvesting of Saffron Using Integer Programming," International Journal of Agricultural Management and Development (IJAMAD), Iranian Association of Agricultural Economics, vol. 10(3), September.
    • Handle: RePEc:ags:ijamad:335133
    DOI: 10.22004/ag.econ.335133
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/335133/files/IJAMAD_Volume%2010_Issue%203_Pages%20307-321.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.335133?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
    ---><---

    References listed on IDEAS

    as
    1. Goel, Asvin & Meisel, Frank, 2013. "Workforce routing and scheduling for electricity network maintenance with downtime minimization," European Journal of Operational Research, Elsevier, vol. 231(1), pages 210-228.
    2. Castillo, Ignacio & Joro, Tarja & Li, Yong Yue, 2009. "Workforce scheduling with multiple objectives," European Journal of Operational Research, Elsevier, vol. 196(1), pages 162-170, July.
    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. Si, Guojin & Xia, Tangbin & Gebraeel, Nagi & Wang, Dong & Pan, Ershun & Xi, Lifeng, 2022. "A reliability-and-cost-based framework to optimize maintenance planning and diverse-skilled technician routing for geographically distributed systems," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    2. Sanja Petrovic, 2019. "“You have to get wet to learn how to swim” applied to bridging the gap between research into personnel scheduling and its implementation in practice," Annals of Operations Research, Springer, vol. 275(1), pages 161-179, April.
    3. Nguyen, Ho Si Hung & Do, Phuc & Vu, Hai-Canh & Iung, Benoit, 2019. "Dynamic maintenance grouping and routing for geographically dispersed production systems," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 392-404.
    4. Paraskevopoulos, Dimitris C. & Laporte, Gilbert & Repoussis, Panagiotis P. & Tarantilis, Christos D., 2017. "Resource constrained routing and scheduling: Review and research prospects," European Journal of Operational Research, Elsevier, vol. 263(3), pages 737-754.
    5. Soares, Ricardo & Marques, Alexandra & Amorim, Pedro & Parragh, Sophie N., 2024. "Synchronisation in vehicle routing: Classification schema, modelling framework and literature review," European Journal of Operational Research, Elsevier, vol. 313(3), pages 817-840.
    6. Schönberger, Jörn, 2017. "Implicit time windows and multi-commodity mixed-fleet vehicle routing," Discussion Papers 1/2017, Technische Universität Dresden, "Friedrich List" Faculty of Transport and Traffic Sciences, Institute of Transport and Economics.
    7. Kaan Kuzu & Refik Soyer, 2018. "Bayesian modeling of abandonments in ticket queues," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(6-7), pages 499-521, September.
    8. Drent, Collin & Keizer, Minou Olde & Houtum, Geert-Jan van, 2020. "Dynamic dispatching and repositioning policies for fast-response service networks," European Journal of Operational Research, Elsevier, vol. 285(2), pages 583-598.
    9. Ağralı, Semra & Taşkın, Z. Caner & Ünal, A. Tamer, 2017. "Employee scheduling in service industries with flexible employee availability and demand," Omega, Elsevier, vol. 66(PA), pages 159-169.
    10. Vidal, Thibaut & Laporte, Gilbert & Matl, Piotr, 2020. "A concise guide to existing and emerging vehicle routing problem variants," European Journal of Operational Research, Elsevier, vol. 286(2), pages 401-416.
    11. Ran Liu & Xiaolan Xie, 2018. "Physician Staffing for Emergency Departments with Time-Varying Demand," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 588-607, August.
    12. Stiglic, Mitja & Agatz, Niels & Savelsbergh, Martin & Gradisar, Mirko, 2015. "The benefits of meeting points in ride-sharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 36-53.
    13. Li, Yulong & Zhang, Chi & Jia, Chuanzhou & Li, Xiaodong & Zhu, Yimin, 2019. "Joint optimization of workforce scheduling and routing for restoring a disrupted critical infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    14. Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
    15. Defraeye, Mieke & Van Nieuwenhuyse, Inneke, 2016. "Staffing and scheduling under nonstationary demand for service: A literature review," Omega, Elsevier, vol. 58(C), pages 4-25.
    16. Guastaroba, G. & Côté, J.-F. & Coelho, L.C., 2021. "The Multi-Period Workforce Scheduling and Routing Problem," Omega, Elsevier, vol. 102(C).
    17. Özlem Kaçmaz & Haci Mehmet Alakaş & Tamer Eren, 2019. "Shift Scheduling with the Goal Programming Method: A Case Study in the Glass Industry," Mathematics, MDPI, vol. 7(6), pages 1-22, June.
    18. Urbani, Michele & Brunelli, Matteo & Punkka, Antti, 2023. "An approach for bi-objective maintenance scheduling on a networked system with limited resources," European Journal of Operational Research, Elsevier, vol. 305(1), pages 101-113.
    19. López-Santana, Eduyn & Akhavan-Tabatabaei, Raha & Dieulle, Laurence & Labadie, Nacima & Medaglia, Andrés L., 2016. "On the combined maintenance and routing optimization problem," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 199-214.
    20. Funke, Julia & Kopfer, Herbert, 2016. "A model for a multi-size inland container transportation problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 70-85.

    More about this item

    Keywords

    Crop Production/Industries;

    Statistics

    Access and download statistics

    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:ags:ijamad:335133. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/iraesea.html .

    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.