Optimization of Poultry Feed Composition Using Hybrid Adaptive Genetic Algorithm and Simulated Annealing

Abstract

The highest component in the production cost of the poultry industry is feed cost. The formation of an efficient feed composition is needed because of the increasing price of feed ingredients. Several types of software have been developed to help determine the feed composition, but the price of commercial feed formulation software is quite expensive for most organizations. Hybrid adaptive genetic algorithm and Simulated Annealing were used to calculate poultry feed formulations. This algorithm used a change mechanism of the control parameter in genetic algorithm adaptively to get better results. Simulated Annealing was applied to avoid a local optimum solution produced by the genetic algorithm. The results showed that hybrid adaptive genetic algorithm and Simulated Annealing is better than the classical genetic algorithm.