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Two Aspects of Optimal Diet Determination for Pig Production: Efficiency of Solution and Incorporation of Cost Variation

机译:确定生猪最佳日粮的两个方面:解决方案的效率和成本变动的合并

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摘要

For many decades linear programming has been used to find minimum cost diets, notably in the chicken and pig meat industries. More recently, animal growth models together with nonlinear optimisation methods have been used to find feeding schedules which simultaneously minimise feed costs and maximise market return, so maximising gross margin. Genetic algorithms can handle these problems, albeit slowly. In this paper we study the particular nature of the objective function (for pig meat production) and develop a global optimisation algorithm tailored to its discontinuous structure. We also demonstrate the use of stochastic programming to cope with changing feed costs and changing price at slaughter.
机译:几十年来,线性编程一直被用来寻找最低成本的饮食,特别是在鸡肉和猪肉工业中。最近,动物生长模型与非线性最优化方法一起用于查找饲喂计划,该计划可同时使饲料成本最小化和市场回报最大化,从而使毛利率最大化。遗传算法可以解决这些问题,尽管速度很慢。在本文中,我们研究了目标函数(用于猪肉生产)的特殊性质,并开发了针对其不连续结构的全局优化算法。我们还演示了使用随机编程来应对饲料成本变化和屠宰价格变化的情况。

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