IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v184y2020ics0308521x20307605.html
   My bibliography  Save this article

Economic optimization of feeding and shipping strategies in pig-fattening using an individual-based model

Author

Listed:
  • Davoudkhani, M.
  • Mahé, F.
  • Dourmad, J.Y.
  • Gohin, A.
  • Darrigrand, E.
  • Garcia-Launay, F.

Abstract

Economic results of pig-fattening systems vary greatly and depend mainly on prices of pork and feeds, and pig growth performance (e.g. feed efficiency, slaughter weight, lean percentage). Previous studies revealed that feeding and shipping strategies are critical factors in the economic outputs of pig production. However, they failed to consider both strategies and the variability in pig growth performance simultaneously. Consequently, we developed a new approach to improve the profitability of pig farms by estimating the best compromise among feeding costs, animal performance, and shipping constraints. We used an individual-based bioeconomic model that simulates the growth of each pig according to its biological traits (e.g. feed intake and protein deposition potential) as a function of different feeding and shipping strategies. The optimization problem is solved using an evolutionary algorithm (CMA-ES, covariance matrix adaptation evolution strategy) that manages the objective function, which is discontinuous, non-convex, nonlinear, and multimodal. Various case studies were constructed to investigate the behavior of the optimization procedure. Effects of pork price on optimal strategies were investigated using three different price scenarios: low (1.173 €/kg), medium (1.314 €/kg), and high (1.662 €/kg) pork prices. Optimizing only feeding strategies improved the gross margin per pig by 5.0% while optimizing shipping strategies improved the mean gross margin per pig by 4.7%. Optimizing both feeding and shipping strategies improved the gross margin per fattened pig by 10% (2.88 €/pig, with medium pork price (1.314€/kg)) compared to the common practice on farms in France. Pork price had a limited effect on feeding decisions when optimized alone, but a strong impact on shipping decisions. Economic optimization of pig fattening inconsistently affected the environmental impacts. However, increasing pork price improved the optimized mean gross margin per pig but increased all environmental impacts. To our knowledge, this is the first tool able to optimize both feeding and shipping strategies while considering effects of variability in growth potential among a batch of pigs. These features allow consideration of the interaction effect of feeding and shipping strategies on the economic outputs of the batch, and investigation of the trade-off between production cost and technical performance. This tool should interest the pig sector since it can identify the best feeding and shipping strategies depending on the economic context. Further work should consider multiobjective optimization with both economic and environmental objectives.

Suggested Citation

  • Davoudkhani, M. & Mahé, F. & Dourmad, J.Y. & Gohin, A. & Darrigrand, E. & Garcia-Launay, F., 2020. "Economic optimization of feeding and shipping strategies in pig-fattening using an individual-based model," Agricultural Systems, Elsevier, vol. 184(C).
    • Handle: RePEc:eee:agisys:v:184:y:2020:i:c:s0308521x20307605
    DOI: 10.1016/j.agsy.2020.102899
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X20307605
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2020.102899?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. Lehmann, Niklaus & Finger, Robert & Klein, Tommy & Calanca, Pierluigi & Walter, Achim, 2013. "Adapting crop management practices to climate change: Modeling optimal solutions at the field scale," Agricultural Systems, Elsevier, vol. 117(C), pages 55-65.
    2. Accatino, Francesco & Tonda, Alberto & Dross, Camille & Léger, François & Tichit, Muriel, 2019. "Trade-offs and synergies between livestock production and other ecosystem services," Agricultural Systems, Elsevier, vol. 168(C), pages 58-72.
    3. Esteve Nadal-Roig & Adela Pagès-Bernaus & Lluís M. Plà-Aragonès, 2018. "Bi-Objective Optimization Model Based on Profit and CO 2 Emissions for Pig Deliveries to the Abattoir," Sustainability, MDPI, vol. 10(6), pages 1-13, May.
    4. Pourmoayed, Reza & Nielsen, Lars Relund & Kristensen, Anders Ringgaard, 2016. "A hierarchical Markov decision process modeling feeding and marketing decisions of growing pigs," European Journal of Operational Research, Elsevier, vol. 250(3), pages 925-938.
    5. Leen, Frederik & Van den Broeke, Alice & Aluwé, Marijke & Lauwers, Ludwig & Millet, Sam & Van Meensel, Jef, 2018. "Stakeholder-driven modelling the impact of animal profile and market conditions on optimal delivery weight in growing-finishing pig production," Agricultural Systems, Elsevier, vol. 162(C), pages 34-45.
    6. Cadero, A. & Aubry, A. & Brun, F. & Dourmad, J.Y. & Salaün, Y. & Garcia-Launay, F., 2018. "Global sensitivity analysis of a pig fattening unit model simulating technico-economic performance and environmental impacts," Agricultural Systems, Elsevier, vol. 165(C), pages 221-229.
    7. Jourdan, L. & Basseur, M. & Talbi, E.-G., 2009. "Hybridizing exact methods and metaheuristics: A taxonomy," European Journal of Operational Research, Elsevier, vol. 199(3), pages 620-629, 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. Verbiest, Floor & Cornelissens, Trijntje & Springael, Johan, 2019. "A matheuristic approach for the design of multiproduct batch plants with parallel production lines," European Journal of Operational Research, Elsevier, vol. 273(3), pages 933-947.
    2. Alejandro del Pozo & Nidia Brunel-Saldias & Alejandra Engler & Samuel Ortega-Farias & Cesar Acevedo-Opazo & Gustavo A. Lobos & Roberto Jara-Rojas & Marco A. Molina-Montenegro, 2019. "Climate Change Impacts and Adaptation Strategies of Agriculture in Mediterranean-Climate Regions (MCRs)," Sustainability, MDPI, vol. 11(10), pages 1-16, May.
    3. Issam-Ali Moindjié & Corentin Pinsard & Francesco Accatino & Raja Chakir, 2022. "Interactions between ecosystem services and land use in France: A spatial statistical analysis [Interactions entre les services écosystémiques et l'utilisation des terres en France : une analyse st," Post-Print hal-03890135, HAL.
    4. Samira Shayanmehr & Jana Ivanič Porhajašová & Mária Babošová & Mahmood Sabouhi Sabouni & Hosein Mohammadi & Shida Rastegari Henneberry & Naser Shahnoushi Foroushani, 2022. "The Impacts of Climate Change on Water Resources and Crop Production in an Arid Region," Agriculture, MDPI, vol. 12(7), pages 1-22, July.
    5. Schönhart, Martin & Mitter, Hermine & Schmid, Erwin & Heinrich, Georg & Gobiet, Andreas, 2014. "Integrated Analysis of Climate Change Impacts and Adaptation Measures in Austrian Agriculture," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 63(3).
    6. Kamdi, Prasad Jairam & Swain, Dillip Kumar & Wani, Suhas P., 2023. "Developing climate change agro-adaptation strategies through field experiments and simulation analyses for sustainable sorghum production in semi-arid tropics of India," Agricultural Water Management, Elsevier, vol. 286(C).
    7. Laura Calvet & Rocio de la Torre & Anita Goyal & Mage Marmol & Angel A. Juan, 2020. "Modern Optimization and Simulation Methods in Managerial and Business Economics: A Review," Administrative Sciences, MDPI, vol. 10(3), pages 1-23, July.
    8. Soroush Kiani Ghalehsard & Javad Shahraki & Ahmad Akbari & Ali Sardar Shahraki, 2021. "Assessment of the impacts of climate change and variability on water resources and use, food security, and economic welfare in Iran," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 14666-14682, October.
    9. Jing Zhu & Shenghong Kang & Wenwu Zhao & Qiujie Li & Xinyuan Xie & Xiangping Hu, 2020. "A Bibliometric Analysis of Food–Energy–Water Nexus: Progress and Prospects," Land, MDPI, vol. 9(12), pages 1-22, December.
    10. Asadabadi, Mehdi Rajabi, 2017. "A customer based supplier selection process that combines quality function deployment, the analytic network process and a Markov chain," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1049-1062.
    11. Framinan, Jose M. & Ruiz, Rubén, 2010. "Architecture of manufacturing scheduling systems: Literature review and an integrated proposal," European Journal of Operational Research, Elsevier, vol. 205(2), pages 237-246, September.
    12. Ghasemi, Mojtaba & Ghavidel, Sahand & Aghaei, Jamshid & Gitizadeh, Mohsen & Falah, Hasan, 2014. "Application of chaos-based chaotic invasive weed optimization techniques for environmental OPF problems in the power system," Chaos, Solitons & Fractals, Elsevier, vol. 69(C), pages 271-284.
    13. Mitter, Hermine & Heumesser, Christine & Schmid, Erwin, 2014. "Modelling robust crop production portfolios to assess agricultural vulnerability to climate change," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182702, European Association of Agricultural Economists.
    14. Ruiz-Meza, José & Montoya-Torres, Jairo R., 2022. "A systematic literature review for the tourist trip design problem: Extensions, solution techniques and future research lines," Operations Research Perspectives, Elsevier, vol. 9(C).
    15. Kannan Govindan, 2016. "Evolutionary algorithms for supply chain management," Annals of Operations Research, Springer, vol. 242(2), pages 195-206, July.
    16. Guido, Rosita & Groccia, Maria Carmela & Conforti, Domenico, 2018. "An efficient matheuristic for offline patient-to-bed assignment problems," European Journal of Operational Research, Elsevier, vol. 268(2), pages 486-503.
    17. Bhattarai, Mukesh Dev & Secchi, Silvia & Schoof, Justin, 2017. "Projecting corn and soybeans yields under climate change in a Corn Belt watershed," Agricultural Systems, Elsevier, vol. 152(C), pages 90-99.
    18. Ashfield, Austen & Mullan, Conall & Jack, Claire, 2020. "Encouraging farmer participation in agricultural education and training: A Northern Ireland perspective," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 9, November.
    19. Meyer-Aurich, Andreas & Gandorfer, Markus & Trost, Benjamin & Ellmer, Frank & Baumecker, Michael, 2016. "Risk efficiency of irrigation to cereals in northeast Germany with respect to nitrogen fertilizer," Agricultural Systems, Elsevier, vol. 149(C), pages 132-138.
    20. Sheng Hang & Jing Li & Xiangbo Xu & Yun Lyu & Yang Li & Huarui Gong & Yan Xu & Zhu Ouyang, 2021. "An Optimization Scheme of Balancing GHG Emission and Income in Circular Agriculture System," Sustainability, MDPI, vol. 13(13), pages 1-15, June.

    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:184:y:2020:i:c:s0308521x20307605. 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.