  Bat algorithm (BA) is a recent optimization algorithm based on swarm
intelligence and inspiration from the echolocation behavior of bats. One of the
issues in the standard bat algorithm is the premature convergence that can
occur due to the low exploration ability of the algorithm under some
conditions. To overcome this deficiency, directional echolocation is introduced
to the standard bat algorithm to enhance its exploration and exploitation
capabilities. In addition to such directional echolocation, three other
improvements have been embedded into the standard bat algorithm to enhance its
performance. The new proposed approach, namely the directional Bat Algorithm
(dBA), has been then tested using several standard and non-standard benchmarks
from the CEC2005 benchmark suite. The performance of dBA has been compared with
ten other algorithms and BA variants using non-parametric statistical tests.
The statistical test results show the superiority of the directional bat
algorithm.
