Non-swarm intelligence search algorithm based on the foraging behaviors of fruit flies

摘要

In the present study, we examine the foraging behavior of the fruit fly (Drosophila), which unlike social insects, independently and autonomously forages. Moreover, we propose a new population-based, non-swarm intelligence search algorithm that mimics the foraging behaviors of fruit flies. We find that the time that a fruit fly stays in a food source region follows a power-law. A power-law distribution satisfies the scale-free property, so the observed behaviors of fruit flies can be called scale-free behaviors, which are modeled by the proposed algorithm. We examine the effect of scale-free behaviors on search performance by applying the proposed algorithm to 28 test functions with two real parameters. The results reveal that the scale-free property is related to a balance between exploration and exploitation and affects the search performance. Moreover, particular parameter values for fixing the scale-free property yield a better search performance for most of the test functions considered herein. The present paper does not provide a competent search algorithm for solving static optimization problems, but rather introduces a novel temporal property of individual behaviors, i.e., a scale-free property, which is expected to provide a new way to think about search algorithms.