Due to limitation of feedstuffs in Mandya, district of Karnataka, small dairy farmers faced many problems to feed balanced, least cost diet to dairy cattle’s. From earlier research it was clear that the productivity of cattle’s maintained by different dairy farmers was lower and this is mainly due tolimited resources for feeding and small farmers are not having proper knowledge as well as resources to provide low cost balanced ration to cattle’s. Therefore, there is a need to focus on minimizing the diet cost by upgrading the scientific dairy farming practices. However, several techniques are in use for animal diet formulation but a successful application of soft computing technique to improve the quality of the solution is always preferred as the rigidity of the functions in Linear Programming Problem (LPP) can be easily handled. Hence, to meet the nutrient requirement,a Primitive Goal programming model for three category of dairy cattle’s weighing 500kg each and yielding 10lit of milk with 4% fat content during 7th, 8th and 9th month of pregnancy is been formulated by dividing the goals into set of priorities. In our earlier work [10], LP models for three categories of dairy cattle’s has been formulated and solved by Simplex-method, GRG Nonlinear, EA-method and RGA. In the present work, a goal programming model (GP model) has been developed by dividing each goal into set of priorities for all the three categories of animal as there are two high priority objectives i.e. least cost and dry matter intake, to be achieved if possible. This GP model is solved by real coded genetic algorithm with hybrid function, which shows thatfive goals are overachieved whereas one goal is fully achieved and one is underachieved for Cattle 1& 2. It could be concluded that real coded genetic algorithm (RGA) with hybrid function can effectively be used to formulate least cost diet such that the feed requirements of the animals are met without any nutrients deficiency.
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