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# Linear with sensitivity analysis, stochastic and goal programming approaches on broiler-breeder chicken feed formulation for Medvil Farms Incorporation/ Ester Mace M. Vilela.

Material type: TextLanguage: English Publication details: 2009Description: 98 leavesSubject(s): Dissertation note: Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2009 Summary: This paper applied three programming methods (linear, goal and stochastic) in minimizing feed ration cost in attaining nutritional requirements of broiler-breeder chickens at different stages. First, a linear programming (LP) model on the formulation of broiler-breeders feed ration was initiated as to basic mathematical model. Specific bounds and constraints were implemented. Constraints for the model were energy, crude, protein, calcium, available phosphorous, linoleic acid, lysine, mmethionine, met+cys, threonine and tryptophan. Sensitivity analysis was done to further explain the coefficients of the LP model. Second, a stochastic programming model (SP), using the initial LP formulation was developed LP model, using its mean value for its coefficients restricts the data and does not handle variability of the ingredients. As a result, the deterministic equivalent model derived from the chance constraint programming model for the SP model was developed and produced more nutritious ration compared to LP. SP utilized all ingredients while LP models have no soybean meal and di-calcium phosphate contribution. Third, a goal programming model (GP) was formulated to handle deviation minimization of the objective function. The first objective is to minimize the cost and the second and the third objective deals with minimizing protein nutrient variability of a 100kilogram ration. GP utilized the ration cost budget of SP making flexible alternative to the shortcomings of LP. The positive deviations from the goal for starter, grower, pre-lay and layer were 68.84339, 66.90413, 63.29819, and 49.80724 respectively. Layer stage, having the smallest value, is the most balanced ration among the four stages. The SP and GP transformation finalize the rations for their optimum feed formula capacity
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Item type Current library Collection Call number Status Date due Barcode
Thesis University Library Non-Circulation LG993.5 2009 A64 V56 (Browse shelf(Opens below)) Available 3UPML00033173
Thesis University Library Non-Circulation LG993.5 2009 A64 V56 (Browse shelf(Opens below)) Available 3UPML00012511

Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2009

This paper applied three programming methods (linear, goal and stochastic) in minimizing feed ration cost in attaining nutritional requirements of broiler-breeder chickens at different stages. First, a linear programming (LP) model on the formulation of broiler-breeders feed ration was initiated as to basic mathematical model. Specific bounds and constraints were implemented. Constraints for the model were energy, crude, protein, calcium, available phosphorous, linoleic acid, lysine, mmethionine, met+cys, threonine and tryptophan. Sensitivity analysis was done to further explain the coefficients of the LP model. Second, a stochastic programming model (SP), using the initial LP formulation was developed LP model, using its mean value for its coefficients restricts the data and does not handle variability of the ingredients. As a result, the deterministic equivalent model derived from the chance constraint programming model for the SP model was developed and produced more nutritious ration compared to LP. SP utilized all ingredients while LP models have no soybean meal and di-calcium phosphate contribution. Third, a goal programming model (GP) was formulated to handle deviation minimization of the objective function. The first objective is to minimize the cost and the second and the third objective deals with minimizing protein nutrient variability of a 100kilogram ration. GP utilized the ration cost budget of SP making flexible alternative to the shortcomings of LP. The positive deviations from the goal for starter, grower, pre-lay and layer were 68.84339, 66.90413, 63.29819, and 49.80724 respectively. Layer stage, having the smallest value, is the most balanced ration among the four stages. The SP and GP transformation finalize the rations for their optimum feed formula capacity

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