Application of real coded genetic algorithm (RGA) to find least cost feedstuffs for dairy cattle during pregnancy

Abstract

The dairy farmers are having limitations in terms of “feedstuffs” available in the tropical region. To meet nutrients requirement at cheapest cost feedstuff need a software programme. There are several techniques/software’s is been adopted to meet nutrient requirement of dairy animal. However, there is no particular techniques is suitable for formulating ration in least cost manner for dairy cattle. Real coded genetic algorithm (RGA) is better approach than conventional methods as unlike older techniques, it is not easily break even if the inputs are modified and RGA gives significant benefits over large and complex optimization techniques even if it is linear programming problem. Hence, a comparative study was planned with embassies on RGA to find suitable technique, which is farmer’s friendly to be adopted at farm level. Materials and Methods: The linear programming model (simplex LP, GRG non-linear, Evolutionary Algorithm (EA) and RGA with and without seeding the random number generations) were executed and compared for least cost feed formulation techniques with adopting three different types of cattle’s weighing 500 kg each and yielding 10 L milk with 4% of fat content during 7th, 8th and 9th months of pregnancy and considering nutrient requirement on dry matter basis. Results: The linear programming model is been solved by simplex LP, GRG non-linear, EA method and RGA with and without seeding the random number generations. There was no significance difference (p>0.05) found with various techniques adopted for feed formulation. However, there will be a better scope for RGA to formulate feed for dairy animals with limited resources at Indian scenario. Conclusion: It could be concluded that real coded genetic algorithm (RGA) can also be used for ration formulation to find least cost feed stuffs in dairy cattle, also we are able to economize the total mixed ration cost such that the feed requirements of the animals are met without any nutrients deficiency.