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.

A modified bats echolocation-based algorithm for solving constrained optimisation problems

“…A MABSA has been proposed for solving constrained optimisation problems. The MABSA has been formulated as an improved version of ABSA developed by Yahya et al (2016). In addition to redefining ABSA parameters, a new strategy, namely the bounce back strategy as a mechanism to control the transmitted beam to fall only within the designated search space, has been incorporated into MABSA.…”

“…ABSA was introduced by Yahya et al (2016) to solve unconstrained single objective optimisation problems. But, to deal with constrained single objective optimisation problems, a crucial problem on how to incorporate the inequality constraints as well as equality constraints with the objective function must be tackled appropriately.…”

“…This section will elaborate solely of these three elements. The other components of MABSA will not be further discussed here as they are similar to the ABSA as presented in Yahya et al (2016).…”

“…This paper introduces a new swarm intelligence algorithm, the so called modified adaptive bats sonar algorithm (MABSA) which is an improved version of the original adaptive bats sonar algorithm (ABSA) by Yahya et al (2016). The algorithm is inspired from bat sonar used in bats echolocation to find prey.…”

Preliminary evaluation of effect of two visual aid devices on navigation in blind dogs

“…The bat is a well‐known example of how echolocation can be used to navigate and detect objects (prey) without vision (Yahya et al . ). By computing the time of reflection of different echoes the bat can recognise the object and its distance.…”