title: A new bats echolocation-based algorithm for single objective optimisation.
abstract: Bats sonar algorithm (BSA) as a swarm intelligence approach utilises the concept of echolocation of bats to find prey. However, the algorithm is unable to achieve good precision and fast convergence rate to the optimum solution. With this in mind, an adaptive bats sonar algorithm is introduced with new paradigms of real bats echolocation behaviour. The performance of the algorithm is validated through rigorous tests with several single objective optimisation benchmark test functions. The obtained results show that the proposed scheme outperforms the BSA in terms of accuracy and convergence speed and can be efficiently employed to solve engineering problems.
authors.affiliation: Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK.
authors.forename: Nafrizuan Mat
authors.initials: NM
authors.lastname: Yahya
authors.affiliation: Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK.
authors.forename: M Osman
authors.initials: MO
authors.lastname: Tokhi
authors.affiliation: Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK.
authors.forename: Hyreil Anuar
authors.initials: HA
authors.lastname: Kasdirin
keywords: Adaptive bats sonar algorithm; Bats echolocation; Bats sonar algorithm; Optimisation; Reciprocal altruism