IDEAS home Printed from https://ideas.repec.org/p/ags/gewi17/262155.html
   My bibliography  Save this paper

Bildung Einer Kostenfunktion Für Die Ausbringung Von Düngemitteln Unter Berücksichtigung Einer Tourenplanungsroutine Mit Teillieferungen (Sdvrp)

Author

Listed:
  • Tröster, Michael

Abstract

Für mathematische Optimierungsmodelle sind Produktionskosten als Restriktionen zu berücksichtigen. Die Funktionsform ist dabei entscheidend für die Abbildung der Kosten, aber auch für den Ressourcenbedarf im Rahmen der Optimierung. In diesem Kontext dokumentiert der vorliegende Beitrag die Erarbeitung einer Kostenfunktion für die Ausbringung von Düngemitteln. Die Ausbringkosten für Düngemittel spielen eine wichtige Rolle für die Auswahl einer Düngestrategie. Mit der Arbeit soll bewertet werden, ob eine exakte Abbildung der Ausbringkosten, im Vergleich zu einer Schätzfunktion, Einfluss auf die Auswahl der Düngestrategie und die erforderliche Rechenleistung hat. Eine vergleichbare Untersuchung, über diesen Trade-off aus Präzision, Rechenleistung und dem möglichem Einfluss auf eine zu optimierenden Düngestrategie, steht derzeit nicht zur Verfügung. Um die Kostenfunktion abzuleiten, wurde sie zunächst in Teilfunktionen zerlegt Eine Herausforderung stellt die Ermittlung des Zeitbedarfs für Transportfahrten dar. Hierzu werden zwei Möglichkeiten gegenübergestellt: Die Berechnung der minimalen Transportzeiten durch ein „Split Delivery Vehicle Routing Problem“ (SDVRP-Modell), bzw. die Schätzung der Transportzeiten mit Hilfe eines linearen Regressionsmodells. Dieses wiederum baut auf Ergebnissen randomisierter SDVRP-Modelläufe auf. Die Ergebnisse dieser Arbeit zeigen, dass die Optimierung der Düngestrategie, unabhängig von der Auswahl der Kostenfunktion, zu einer einheitlichen Lösung führt. Steht die Optimierung der Düngestrategie im Vordergrund, kann daher auf die vereinfachte Schätzung der Transportzeit mit Hilfe des linearen Regressionsmodells zurückgegriffen werden.

Suggested Citation

  • Tröster, Michael, 2017. "Bildung Einer Kostenfunktion Für Die Ausbringung Von Düngemitteln Unter Berücksichtigung Einer Tourenplanungsroutine Mit Teillieferungen (Sdvrp)," 57th Annual Conference, Weihenstephan, Germany, September 13-15, 2017 262155, German Association of Agricultural Economists (GEWISOLA).
  • Handle: RePEc:ags:gewi17:262155
    DOI: 10.22004/ag.econ.262155
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/262155/files/Troester_122.pdf
    Download Restriction: no

    File URL: https://ageconsearch.umn.edu/record/262155/files/Troester_122.pdf?subformat=pdfa
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.262155?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. Rose, David C. & Sutherland, William J. & Parker, Caroline & Lobley, Matt & Winter, Michael & Morris, Carol & Twining, Susan & Ffoulkes, Charles & Amano, Tatsuya & Dicks, Lynn V., 2016. "Decision support tools for agriculture: Towards effective design and delivery," Agricultural Systems, Elsevier, vol. 149(C), pages 165-174.
    2. Jin, Mingzhou & Liu, Kai & Bowden, Royce O., 2007. "A two-stage algorithm with valid inequalities for the split delivery vehicle routing problem," International Journal of Production Economics, Elsevier, vol. 105(1), pages 228-242, January.
    3. Moshe Dror & Pierre Trudeau, 1990. "Split delivery routing," Naval Research Logistics (NRL), John Wiley & Sons, vol. 37(3), pages 383-402, June.
    4. C. Archetti & M. G. Speranza & A. Hertz, 2006. "A Tabu Search Algorithm for the Split Delivery Vehicle Routing Problem," Transportation Science, INFORMS, vol. 40(1), pages 64-73, February.
    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. Jianli Shi & Jin Zhang & Kun Wang & Xin Fang, 2018. "Particle Swarm Optimization for Split Delivery Vehicle Routing Problem," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(02), pages 1-42, April.
    2. Leonardo Berbotto & Sergio García & Francisco Nogales, 2014. "A Randomized Granular Tabu Search heuristic for the split delivery vehicle routing problem," Annals of Operations Research, Springer, vol. 222(1), pages 153-173, November.
    3. Nicola Bianchessi & Michael Drexl & Stefan Irnich, 2019. "The Split Delivery Vehicle Routing Problem with Time Windows and Customer Inconvenience Constraints," Transportation Science, INFORMS, vol. 53(4), pages 1067-1084, March.
    4. Bortfeldt, Andreas & Yi, Junmin, 2020. "The Split Delivery Vehicle Routing Problem with three-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 282(2), pages 545-558.
    5. Lin, Yen-Hung & Batta, Rajan & Rogerson, Peter A. & Blatt, Alan & Flanigan, Marie, 2011. "A logistics model for emergency supply of critical items in the aftermath of a disaster," Socio-Economic Planning Sciences, Elsevier, vol. 45(4), pages 132-145, December.
    6. Han, Anthony Fu-Wha & Chu, Yu-Ching, 2016. "A multi-start heuristic approach for the split-delivery vehicle routing problem with minimum delivery amounts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 11-31.
    7. Saman Eskandarzadeh & Reza Tavakkoli-Moghaddam & Amir Azaron, 2009. "An extension of the relaxation algorithm for solving a special case of capacitated arc routing problems," Journal of Combinatorial Optimization, Springer, vol. 17(2), pages 214-234, February.
    8. Gizem Ozbaygin & Oya Karasan & Hande Yaman, 2018. "New exact solution approaches for the split delivery vehicle routing problem," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 85-115, March.
    9. Lavigne, Carolien & Inghels, Dirk & Dullaert, Wout & Dewil, Reginald, 2023. "A memetic algorithm for solving rich waste collection problems," European Journal of Operational Research, Elsevier, vol. 308(2), pages 581-604.
    10. Yugang Yu & Chengbin Chu & Haoxun Chen & Feng Chu, 2012. "Large scale stochastic inventory routing problems with split delivery and service level constraints," Annals of Operations Research, Springer, vol. 197(1), pages 135-158, August.
    11. Berbotto, Leonardo & García, Sergio & Nogales, Francisco J., 2011. "A vehicle routing model with split delivery and stop nodes," DES - Working Papers. Statistics and Econometrics. WS ws110906, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Ferrer, Laia & Pastor, Rafael & García-Villoria, Alberto, 2009. "Designing salespeople's routes with multiple visits of customers: A case study," International Journal of Production Economics, Elsevier, vol. 119(1), pages 46-54, May.
    13. Guy Desaulniers, 2010. "Branch-and-Price-and-Cut for the Split-Delivery Vehicle Routing Problem with Time Windows," Operations Research, INFORMS, vol. 58(1), pages 179-192, February.
    14. Cortes, Juan David & Suzuki, Yoshinori, 2020. "Vehicle Routing with Shipment Consolidation," International Journal of Production Economics, Elsevier, vol. 227(C).
    15. Salani, Matteo & Vacca, Ilaria, 2011. "Branch and price for the vehicle routing problem with discrete split deliveries and time windows," European Journal of Operational Research, Elsevier, vol. 213(3), pages 470-477, September.
    16. C. Archetti & M. Bouchard & G. Desaulniers, 2011. "Enhanced Branch and Price and Cut for Vehicle Routing with Split Deliveries and Time Windows," Transportation Science, INFORMS, vol. 45(3), pages 285-298, August.
    17. Jeroen Ooge & Katrien Verbert, 2022. "Visually Explaining Uncertain Price Predictions in Agrifood: A User-Centred Case-Study," Agriculture, MDPI, vol. 12(7), pages 1-25, July.
    18. Paul Stefan MARKOVITS, 2024. "Assesing Romanian Farmers’ Motivation For Digitalization: A Unified Theory Of Acceptance And Usage Of Technology (Utaut) Based Research Model," Oradea Journal of Business and Economics, University of Oradea, Faculty of Economics, vol. 9(1), pages 98-112, March.
    19. Puca Huachi Vaz Penna & Anand Subramanian & Luiz Satoru Ochi & Thibaut Vidal & Christian Prins, 2019. "A hybrid heuristic for a broad class of vehicle routing problems with heterogeneous fleet," Annals of Operations Research, Springer, vol. 273(1), pages 5-74, February.
    20. Michael E. Fragkos & Vasileios Zeimpekis & Vasilis Koutras & Ioannis Minis, 2022. "Supply planning for shelters and emergency management crews," Operational Research, Springer, vol. 22(1), pages 741-777, March.

    More about this item

    Keywords

    Farm Management; Production Economics;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:gewi17:262155. 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/gewisea.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.