Extending the bat foraging metaphor for optimisation algorithm design

A particular feature of most species of bats is that they use echolocation, or ‘active sensing’, in which pulses of acoustic energy are emitted and the resulting echo is resolved into an ‘image’ of their surrounding environment. This is used to detect objects and to locate food resources such as flying insects. Previous work has taken inspiration from the process of echolocation to develop the ‘bat algorithm’ (Yang, 2010) and this has demonstrated good results on a wide range of optimisation problems. In this paper we build on this work in order to stimulate further interest in exploration of a bat foraging metaphor as an inspiration for the design of optimisation algorithms. This study provides a review of some recent relevant literature on bat foraging and uncovers several aspects of the foraging process which have not been given explicit consideration in bat algorithm design thus far. We also outline a general framework of foraging behaviour which distinguishes between the role of ‘perception’, ‘memory’, and the use of the ‘social’ information available to a foraging bat. We demonstrate how some of these features can be integrated into an exemplar optimisation algorithm and test the performance of this algorithm on a series of benchmark problems. The study also provides several ideas for future work.