Maximisation of gross margin in intensive livestock production

P. C H Morel, D. L J Alexander, R. L. Sherriff, G. R. Wood

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

    2 Citations (Scopus)

    Abstract

    Diets for intensive pig and poultry farming have traditionally been formulated by minimising feed cost while satisfying certain nutritional constraints. More recently, computerised growth models have allowed rapid simulation of the effects of various dietary programmes on total gross margin. This approach is now extended, by solving the diet formulation problem using developments in the field of mathematical optimisation. In this way, more realistic and complex models of the farming situation can be treated. The advantages of this solution process are demonstrated via analysis of the objective function and comparison with a pure random search method. Application of the results and some limitations of the material in this paper are also discussed.

    Original languageEnglish
    Title of host publicationII International Symposium on Application of Modelling as an Innovative Technology in the Agri-Food Chain; MODEL-IT
    Place of PublicationLeuven
    PublisherInternational Society for Horticultural Science
    Pages97-103
    Number of pages7
    Volume566
    ISBN (Electronic)9066057556
    ISBN (Print)9789066057555
    DOIs
    Publication statusPublished - Dec 2001
    EventSecond international symposium on applications of modelling as an innovative technology in the agri-food chain - Palmerston North, New Zealand
    Duration: 9 Dec 200113 Dec 2001

    Publication series

    NameActa Horticulturae
    Volume566
    ISSN (Print)05677572

    Conference

    ConferenceSecond international symposium on applications of modelling as an innovative technology in the agri-food chain
    Country/TerritoryNew Zealand
    CityPalmerston North
    Period9/12/0113/12/01

    Keywords

    • Ascent method
    • Genetic algorithm
    • Growth model
    • Linear programming
    • Monte carlo
    • Nelder-mead algorithm
    • Simulated annealing
    • Tabu search

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