Near Real-time Performance of Population-based Nature-Inspired Algorithms on Cheaper and Older Smartphones

For solving optimization problems, stochastic population-based nature-inspired algorithms use inspirations from nature. Despite their applicability in real-world environments, their bottleneck is high time complexity. Usually, they are searching for optimal solutions on computing devices of full computational power. However, in some situations, we deal with devices of limited computational power. Some examples of such devices are smartphones, which have been becoming very powerful for running various applications. However, there is still a lack of researches that would study the performance of nature-inspired algorithms on these devices. In this paper, we analyze the performance of one member of the nature-inspired algorithms, the so-called Bat algorithm, on the Android smartphone. Although smartphones nowadays offer a computational power comparable with the personal computer, we focus on the cheaper and older smartphones that are most widespread today.