Cost optimization of feed mixes by genetic algorithms

The cost optimization is a key element to determine the least-cost feed mixture according to animals' nutrient requirements and the effective use of the sources. In this paper, the cost optimization of feeds is performed by genetic algorithm, considering the growing style and type, age, nutritional requirement and feedstuff costs for poultry and different types of animals. The proposed method is compared with linear programming approach to measure its performance. The obtained results show that Genetic algorithms could be applicable to the cost optimization of the feed mixtures. In addition, a software program is developed by using Delphi environment, which provides flexible, extensible and user-friendly framework for tuning the heuristic relevant parameters and improving the solution quality.