Evaluation of a Novel Bees Algorithm for Improvement of Genetic Algorithms in a Classification Model

Abstract

A major issue which divides the colony insects algorithms from the classical Genetic Algorithms is higher performance of the those natural based algorithms in comparison with the classical types. Processing times, Local optima problem and low accuracy in the complex optimization problems are the most important lacks of classical Genetic Algorithms. In this article a novel hybrid Bees Algorithm is proposed to optimizes the performance of a Fuzzy classification while the limited raw input data as the features are used. In this model, the proposed Bees Algorithm simulates the honey bees behaviour in the offspring generation process called Bee Royalty Offspring Algorithm (BROA) to improve the training process of classic Genetic Algorithm. The evaluation results illustrated that the BROA improves considerably the accuracy rate and the performance of the training process of classical Genetic Algorithms.