A Systematic Review on Bat Algorithm: Theoretical Foundation, Variants, and Applications

Bat algorithm (BA) is a population-based metaheuristic algorithm inspired by echolocation behavior of bat. After the development of BA in 2010, it becomes the attention of researchers from various domains. It has been successfully applied in various real-life engineering problems. This paper presents a comprehensive review of BA. The biological inspiration and working of BA are deliberated. The variants of BA namely improved, hybrid, levy flight, chaotic, binary, and multiobjective are analyzed in detail. The applications of BA in different research domains are investigated. The current challenges and future research directions of BA are discussed. Besides highlighting the new developments in structure of BA, this study can be act as a baseline for young researchers to enhance the performance of their metaheuristic algorithms on adapting the BA. This study will encourage the young researchers and scientists to use BA in their research problems.

Automated summary

The bat algorithm, inspired by echolocation behavior, has been successfully applied in various engineering problems and attracted attention from researchers. This paper provides a comprehensive review and analysis of BA, discussing its biological inspiration, working principles, variants, and applications in different research domains. Moreover, it also highlights current challenges, future research directions, and serves as a baseline for improving metaheuristic algorithms.