Multiobjective stochastic programming for feed formulation
The minimum cost linear programming model used traditionally for feed formulation does not take account of variability of nutrients in feed ingredients. Therefore, it may be that the nutrient requirements of the animal are not adequately met. In this paper, we show how a multiobjective stochastic mo...
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| Published in: | The Journal of the Operational Research Society Vol. 60; no. 12; pp. 1738 - 1748 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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London
Taylor & Francis
01.12.2009
Palgrave Macmillan Palgrave Macmillan UK Taylor & Francis Ltd |
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| ISSN: | 0160-5682, 1476-9360 |
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| Abstract | The minimum cost linear programming model used traditionally for feed formulation does not take account of variability of nutrients in feed ingredients. Therefore, it may be that the nutrient requirements of the animal are not adequately met. In this paper, we show how a multiobjective stochastic model that permits confronting the cost of the ration with the probabilities of meeting the nutrient requirements of the animal can enhance the process of animal diet formulation. The model presented here does not require any a priori information from the decision maker, eliciting his preferences through an interactive process. This is the main advantage in relation to other models found in the literature for treating the problem of nutrient variability, which introduce stochastic constraints in the single objective minimum cost model requiring fixing the level of probability desired for each one of the nutrients in advance. |
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| AbstractList | The minimum cost linear programming model used traditionally for feed formulation does not take account of variability of nutrients in feed ingredients. Therefore, it may be that the nutrient requirements of the animal are not adequately met. In this paper, we show how a multiobjective stochastic model that permits confronting the cost of the ration with the probabilities of meeting the nutrient requirements of the animal can enhance the process of animal diet formulation. The model presented here does not require any a priori information from the decision maker, eliciting his preferences through an interactive process. This is the main advantage in relation to other models found in the literature for treating the problem of nutrient variability, which introduce stochastic constraints in the single objective minimum cost model requiring fixing the level of probability desired for each one of the nutrients in advance. The minimum cost linear programming model used traditionally for feed formulation does not take account of variability of nutrients in feed ingredients. Therefore, it may be that the nutrient requirements of the animal are not adequately met. In this paper, we show how a multiobjective stochastic model that permits confronting the cost of the ration with the probabilities of meeting the nutrient requirements of the animal can enhance the process of animal diet formulation. The model presented here does not require any a priori information from the decision maker, eliciting his preferences through an interactive process. This is the main advantage in relation to other models found in the literature for treating the problem of nutrient variability, which introduce stochastic constraints in the single objective minimum cost model requiring fixing the level of probability desired for each one of the nutrients in advance. The minimum cost linear programming model used traditionally for feed formulation does not take account of variability of nutrients in feed ingredients. Therefore, it may be that the nutrient requirements of the animal are not adequately met. In this paper, we show how a multiobjective stochastic model that permits confronting the cost of the ration with the probabilities of meeting the nutrient requirements of the animal can enhance the process of animal diet formulation. The model presented here does not require any a priori information from the decision maker, eliciting his preferences through an interactive process. This is the main advantage in relation to other models found in the literature for treating the problem of nutrient variability, which introduce stochastic constraints in the single objective minimum cost model requiring fixing the level of probability desired for each one of the nutrients in advance. [PUBLICATION ABSTRACT] |
| Author | Castrodeza, C Lara, P Peña, T |
| Author_xml | – sequence: 1 givenname: T surname: Peña fullname: Peña, T email: maitepe@eco.uva.es organization: University of Valladolid – sequence: 2 givenname: P surname: Lara fullname: Lara, P organization: University of Córdoba – sequence: 3 givenname: C surname: Castrodeza fullname: Castrodeza, C email: maitepe@eco.uva.es organization: University of Valladolid |
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| Copyright | Copyright © 2008, Palgrave Macmillan 2008 Copyright 2009 Operational Research Society Ltd Palgrave Macmillan 2008 2015 INIST-CNRS Palgrave Macmillan 2009 |
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| Keywords | agriculture multi-objective fractional programming stochastic programming Stochastic model Probabilistic approach Decision making Variability Multiobjective programming Machine feed Linear programming Modeling Linear model Stochastic programming Diet Preference Agriculture Fractional programming Rational function |
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| SubjectTerms | agriculture Animals Applied sciences Approximation Business and Management Decision theory. Utility theory Diet Dietary minerals Economic costs Exact sciences and technology Feed formulation Feed science Feeds Fish byproducts Ingredients Linear programming Management Mathematical programming Minimization of cost multi-objective fractional programming Normal distribution Nutrients Nutritional requirements Operational research and scientific management Operational research. Management science Operations research Operations Research/Decision Theory Probability Random variables Safety factors Standard deviation Stochastic models stochastic programming Studies Swine Theoretical Paper Theoretical Papers |
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| Title | Multiobjective stochastic programming for feed formulation |
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