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Linear programming techniques have been extensively used for animal diet formulation for more than last fifty years. To overcome the drawback of linear approximation of objective function for diet formulation, a mathematical model based on nonlinear programming technique is proposed to measure animal performance in terms of milk yield and weight gain. At the second step, it compares the result of proposed program with that of linear programming model. Result of proposed model gives better results using nonlinear programming. Thus the study is an attempt to develop a nonlinear programming model for optimal planning and best use of nutrient ingredients.

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This paper presents algorithms for simulation tool development to formulate and compute cattle diet at different stages of livestock. Algorithms are proposed for bi-criteria models. The objectives taken are minimization of cost and maximization of the shelf life of animal feed mix. Other objectives achieved by these algorithms are inclusion of nutrient variability in the feed mix and minimization of the deviations. For developing the algorithms, combination of three mathematical programming techniques: linear, stochastic and goal programming is used. Computational and technological interface is included in the field of animal diet formulation by developing the algorithms, which provides better and faster results. Twenty mathematical models are solved by proposed algorithms and obtained results showed superiority of algorithm 2 in terms of nutrient variability whereas algorithm 1 provides better results in terms of lesser cost and more shelf life. Algorithm 3 is taking the two objectives in parallel and providing the optimal feed mix at minimum deviations from the target values of the cost and the shelf life.

In this paper, nonlinear effects of nutrient ingredients are introduced as an approach closer to the true effects of nutrient ingredients. A nonlinear model is developed to take consideration of nutrient ingredients more effectively. The nonlinear model is introduced in order to maximize the weight gain in buffalo by the optimal use of feed ingredients. Data from a variable caloric density study for buffalo is fitted to nonlinear objective function expression for weight gain of the animal in terms of feed ingredients. National Research Council requirements are introduced as constraints for mathematical model. Proposed model with nonlinear programming measures its performance and gives a comparative result with linear programming models. Thus the study is an attempt to develop a nonlinear programming model for optimal planning and best use of nutrient ingredients.