Performance Study of Bat Algorithm Running on Embedded Hardware

Bat algorithm belongs to a class of swarm intelligence algorithms. Comparing to the other stochastic nature-inspired population-based algorithms, this has always been considered as computationally inexpensive. Due to its simplicity and effectiveness, it is very popular in scientific community by solving various optimization problems. However, not enough devotion has been performed on the behaviour of this algorithm running on embedded hardware. In this paper, we look for an answer about the performance of bat algorithm running on three different Raspberry Pi devices of limited performances. In line with this, we conduct a series of experiments by solving the benchmark suite consisting of 10 functions. Because of achieving the similar quality of solutions on all observed hardware, thus, the execution times have been measured.