Interactive total mixed ration formulation using differential evolution

Animal protein provides important sources of nutrients to humans worldwide. About 60 to 80% of production costs are incurred by animal feed which is dependent on the breed, class and phase of the animal. This is a non-deterministic polynomial-time hardness recurrent problem due to the existence of various constraints. Satisfying constraints at specific stages of breeding are often not possible for most programming tools as this entails the development of programs with intrinsic mechanisms to allow easing of constraints based on the necessities of users. Consequently, the formulation of the problems and systems of optimization should facilitate this. The conventional formulations were modified using tolerance parameters that enables constraints relaxation. A method of differential evolution, a variant of evolutionary algorithms with epsilon constraint handling is proposed. Results of our experimental trials indicated that easing requirements has direct connections with the cost and in some instances, quantity of feed. We propose a system which possesses the capability to explore for an optimal or best solution to satisfy the constraints and find the suitable components to be used in the formulation.