IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v148y2016icp114-123.html
   My bibliography  Save this article

Resource allocation in pastoral dairy production systems: Evaluating exact and genetic algorithms approaches

Author

Listed:
  • Notte, Gastón
  • Pedemonte, Martín
  • Cancela, Héctor
  • Chilibroste, Pablo

Abstract

The problem of food resources allocation to a heterogeneous dairy herd was studied in this paper. We focused on how to allocate available resources by grouping cows and their subsequent distribution in the field (pasture and/or feeding area). The main goal of this paper was to maximize either milk production or the margin over feeding cost for the entire dairy herd. The input of energy from different feed resources and the animal requirements of energy were considered. A mathematical model and a Genetic Algorithm (GA) were programmed. An experimental evaluation was performed in order to analyze the quality solution of the GA and to study how the resource allocation should be performed by interpreting the solutions' structure for both methods. The diversity of the solutions provided by the GA was also studied. The experimental evaluation showed that the gap values (milk production difference) between the GA and the Exact Method (EM) solutions were smaller than 2%. Also, when food resources were scarce, there was a great difference (almost a 50% difference for a herd of 1500 cows) between the GA and the EM solutions' structure. The results showed that values obtained by the GA were very close to the values obtained by the exact method, but generating different assignment structures, presenting a good diversity and a wider exploration of the solutions' space.

Suggested Citation

  • Notte, Gastón & Pedemonte, Martín & Cancela, Héctor & Chilibroste, Pablo, 2016. "Resource allocation in pastoral dairy production systems: Evaluating exact and genetic algorithms approaches," Agricultural Systems, Elsevier, vol. 148(C), pages 114-123.
    • Handle: RePEc:eee:agisys:v:148:y:2016:i:c:p:114-123
    DOI: 10.1016/j.agsy.2016.07.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X16303493
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2016.07.009?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. Rehman, Tahir & Romero, Carlos, 1984. "Multiple-criteria decision-making techniques and their role in livestock ration formulation," Agricultural Systems, Elsevier, vol. 15(1), pages 23-49.
    2. Frederick V. Waugh, 1951. "The Minimum-Cost Dairy FeedAn Application of "Linear Programming"," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 33(3), pages 299-310.
    3. Doole, Graeme J. & Romera, Alvaro J., 2013. "Detailed description of grazing systems using nonlinear optimisation methods: A model of a pasture-based New Zealand dairy farm," Agricultural Systems, Elsevier, vol. 122(C), pages 33-41.
    4. Graeme J. Doole & Alvaro J. Romera & Alfredo A. Adler, 2012. "A Mathematical Optimisation Model of a New Zealand Dairy Farm: The Integrated Dairy Enterprise (IDEA) Framework," Working Papers in Economics 12/01, University of Waikato.
    5. Andrés Weintraub & Carlos Romero, 2006. "Operations Research Models and the Management of Agricultural and Forestry Resources: A Review and Comparison," Interfaces, INFORMS, vol. 36(5), pages 446-457, October.
    6. E. L. Lawler & D. E. Wood, 1966. "Branch-and-Bound Methods: A Survey," Operations Research, INFORMS, vol. 14(4), pages 699-719, August.
    7. Dean, G. W. & Carter, H. O. & Wagstaff, H. R. & Olayide, S. O. & Ronning, M. & Bath, D. L., 1972. "Production Functions and Linear Programming Models for Dairy Cattle Feeding," Monographs, University of California, Davis, Giannini Foundation, number 251915, December.
    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. Min, Xinyuan & Sok, Jaap & de Zwart, Feije & Oude Lansink, Alfons, 2024. "Multi-stakeholder multi-objective greenhouse design optimization," Agricultural Systems, Elsevier, vol. 215(C).
    2. Notte, Gastón & Cancela, Héctor & Pedemonte, Martín & Chilibroste, Pablo & Rossing, Walter & Groot, Jeroen C.J., 2020. "A multi-objective optimization model for dairy feeding management," Agricultural Systems, Elsevier, vol. 183(C).
    3. Ipek Kazancoglu & Melisa Ozbiltekin-Pala & Sachin Kumar Mangla & Ajay Kumar & Yigit Kazancoglu, 2023. "Using emerging technologies to improve the sustainability and resilience of supply chains in a fuzzy environment in the context of COVID-19," Annals of Operations Research, Springer, vol. 322(1), pages 217-240, March.

    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. Notte, Gastón & Cancela, Héctor & Pedemonte, Martín & Chilibroste, Pablo & Rossing, Walter & Groot, Jeroen C.J., 2020. "A multi-objective optimization model for dairy feeding management," Agricultural Systems, Elsevier, vol. 183(C).
    2. Addisu H. Addis & Hugh T. Blair & Paul R. Kenyon & Stephen T. Morris & Nicola M. Schreurs, 2021. "Optimization of Profit for Pasture-Based Beef Cattle and Sheep Farming Using Linear Programming: Model Development and Evaluation," Agriculture, MDPI, vol. 11(6), pages 1-16, June.
    3. Dowson, Oscar & Philpott, Andy & Mason, Andrew & Downward, Anthony, 2019. "A multi-stage stochastic optimization model of a pastoral dairy farm," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1077-1089.
    4. J. Žgajnar & L. Juvančič & S. Kavčič, 2009. "Combination of linear and weighted goal programming with penalty function in optimisation of a daily dairy cow ration," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 55(10), pages 492-500.
    5. Rosshairy Abd. Rahman & Graham Kendall & Razamin Ramli & Zainoddin Jamari & Ku Ruhana Ku-Mahamud, 2017. "Shrimp Feed Formulation via Evolutionary Algorithm with Power Heuristics for Handling Constraints," Complexity, Hindawi, vol. 2017, pages 1-12, November.
    6. Andrés Weintraub & Carlos Romero, 2006. "Operations Research Models and the Management of Agricultural and Forestry Resources: A Review and Comparison," Interfaces, INFORMS, vol. 36(5), pages 446-457, October.
    7. Venn, Tyron J. & Dorries, Jack W. & McGavin, Robert L., 2021. "A mathematical model to support investment in veneer and LVL manufacturing in subtropical eastern Australia," Forest Policy and Economics, Elsevier, vol. 128(C).
    8. Coşar Gözükırmızı & Metin Demiralp, 2019. "Solving ODEs by Obtaining Purely Second Degree Multinomials via Branch and Bound with Admissible Heuristic," Mathematics, MDPI, vol. 7(4), pages 1-23, April.
    9. Shumway, C. Richard & Reyes, Alberto A. & Blake, Robert W., 1982. "Profitability And Risks In Dairy Feeding Programs: A Multiperiod Optimization," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 14(2), pages 1-6, December.
    10. Doole, Graeme J. & Romera, Alvaro J., 2014. "Implications of a nitrogen leaching efficiency metric for pasture-based dairy farms," Agricultural Water Management, Elsevier, vol. 142(C), pages 10-18.
    11. Kezong Tang & Xiong-Fei Wei & Yuan-Hao Jiang & Zi-Wei Chen & Lihua Yang, 2023. "An Adaptive Ant Colony Optimization for Solving Large-Scale Traveling Salesman Problem," Mathematics, MDPI, vol. 11(21), pages 1-26, October.
    12. Amine Lamine & Mahdi Khemakhem & Brahim Hnich & Habib Chabchoub, 2016. "Solving constrained optimization problems by solution-based decomposition search," Journal of Combinatorial Optimization, Springer, vol. 32(3), pages 672-695, October.
    13. Torres-Rojo, J. M., 2001. "Risk management in the design of a feeding ration: a portfolio theory approach," Agricultural Systems, Elsevier, vol. 68(1), pages 1-20, April.
    14. Weiqiang Pan & Zhilong Shan & Ting Chen & Fangjiong Chen & Jing Feng, 2016. "Optimal pilot design for OFDM systems with non-contiguous subcarriers based on semi-definite programming," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 63(2), pages 297-305, October.
    15. Mustapha Ouhimmou & Sophie D'Amours & Robert Beauregard & Daoud Ait-Kadi & Satyaveer Singh Chauhan, 2009. "Optimization Helps Shermag Gain Competitive Edge," Interfaces, INFORMS, vol. 39(4), pages 329-345, August.
    16. Konyar, Kazim & Knapp, Keith, 1986. "Demand for Alfalfa Hay in California," Research Reports 251941, University of California, Davis, Giannini Foundation.
    17. Drexl, Andreas, 1990. "Scheduling of project networks by job assignment," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 247, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    18. Yi-Feng Hung & Wei-Chih Chen, 2011. "A heterogeneous cooperative parallel search of branch-and-bound method and tabu search algorithm," Journal of Global Optimization, Springer, vol. 51(1), pages 133-148, September.
    19. Fox, B. L. & Lenstra, J. K. & Rinnooy Kan, A. H. G. & Schrage, L. E., 1977. "Branching From The Largest Upper Bound: Folklore And Facts," Econometric Institute Archives 272158, Erasmus University Rotterdam.
    20. Zgajnar, Jaka & Kavcic, Stane, 2011. "Weighted Goal Programming and Penalty Functions: Whole-farm Planning Approach Under Risk," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 118033, European Association of Agricultural Economists.

    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:eee:agisys:v:148:y:2016:i:c:p:114-123. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agsy .

    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.