Optimization Algorithm Applied to Environmental Control in Broiler Houses

Abstract

The present study aimed to apply the Simulated Annealing (SA) optimization algorithm to find the ideal control of broiler housing rearing environment at 21, 28, 35, and 42 days of growth. Data from four types of houses using environmental control and similar flock density were recorded weekly in the morning and afternoon, during two seasons (summer and winter). The variables related to environmental and air quality data (temperature, relative humidity, air velocity, ammonia, and carbon dioxide concentrations) were registered and organized into the database to provide a descriptive analysis. The ideal rearing conditions were established as a goal, and we used the Simulated Annealing optimization algorithm to process the data. Such an approach may be applied in the cases that the ideal condition of optimization has multiple objectives, and when each variable is the result of a process. The model was implemented considering the optimal controlled environmental condition that depends on the age of broilers. Results indicated that there was a large dispersion of the data collected from the environmental variables. The process suggested that the optimized functions lead to absolute values obtained by the algorithm for each of the environmental factors of the controlled environmental system, representing the optimal condition of the environment found for each broiler age, considering the interactions of the variables. The maximum optimization was prominent to 21 and 35-d old birds, representing 40-48% of the improvement of the process. 28 and 42-d old birds might benefit from the controlled environmental optimization process by up to 30%.