Abstract
A COMPARATIVE STUDY OF PARTICLE SWARM OPTIMIZATION AND GRAVITATIONAL SEARCH ALGORITHM IN POULTRY HOUSE TEMPERATURE CONTROL SYSTEM
B. O. Ola, O. O. Awodoye* and J. P. Oguntoye*
ABSTRACT
Low or unexpected rise in temperature is a major factor affect the effectiveness and productivity of broiler chickens. Maintaining and keeping the temperature at normal level is essential to reducing the mortality rate and increase the productivity of the poultry. Some Nature Inspired Algorithms (NIAs) which have proven to be efficient have been adopted to regulate the temperature of the poultry house. However, various studies have shown that there is no algorithm that can achieve the best solution for all optimization problems, and that some algorithms give a better solution for some problems than the others. Therefore, in this study, a comparative analysis of the Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) in Poultry House Temperature Control System. The experiment results show that both PSO and GSA were able to regulated the poultry house efficiently. However, PSO proved to be more efficient than GSA in terms of cost and computational time. The PSO is able to find better solutions and converges faster compared to the Gravitational Search Algorithm. It is therefore, recommended that PSO should be adopted instead of GSA in poultry house temperature regulation systems.
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