The use of iterative linear programming in practical applications of animal diet formulation
M2SABI Proceedings of the 1st IMACS-IFAC symposium on Mathematical modelling and simulation in agriculture and bio-industries
Practical genetic algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Improving real-parameter genetic algorithm with simulated annealing for engineering problems
Advances in Engineering Software
Genetic algorithms optimization for normalized normal constraint method under Pareto construction
Advances in Engineering Software
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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.