Chaotic Swarm Bat Algorithm with Improved Search

Swarm bat algorithm with improved search (SBAIS) is an efficient modification of the bat algorithm (BA). It works by partitioning the population into a super-swarm of best solutions, and sub-swarms of remaining solutions. The super swarm performs a refined search while remaining swarms perform a standard search as per BA. This partitioning into swarms and use of different search mechanisms helps SBAIS to enhance its performance. In this paper, a chaotic variant of SBAIS, called chaotic swarm bat algorithm with improved search (ChSBAIS) is proposed. Ten different chaotic map functions are tested to enhance SBAIS, and the best one is selected for ChSBAIS. The proposed algorithm is compared to SBAIS over 30 different optimization functions and different dimensions. Results show that using a chaotic map imparts higher efficiency to ChSBAIS, establishing it as a strong optimization algorithm.